About the role 

Roku is looking for a Sr. Data scientist to join the Core Analytics team supporting our Viewer Product team. In this role, you will leverage data analytics to support and improve our Live product. You will own end-to-end analytics that shape how viewers discover, engage with, and return to Live experiences on Roku. You will work closely with product management and engineering to identify opportunities to create new features, drive their adoption, and generate value for Roku. This individual will investigate and develop solutions to track, monitor and improve our ecosystem. The successful candidate is quantitatively driven, detail-focused, and possesses an elevated level of problem-solving expertise. 

What you'll be doing 

• Analyze structured and unstructured data and communicate insights to help stakeholders solve business problems, identify trends and make data-driven decisions 

• Advise on key product development strategy decisions to drive our Live product experience 

• Develop and maintain dashboards, reports, and data visualizations to monitor key metrics for operational and systems health 

• Develop necessary data pipelines to power automation, validation and reporting 

• Collaborate with stakeholders to align data science initiatives with organizational goals and strategy design and execute A/B tests 

• Perform exploratory data analysis on emerging trends and execute advanced analysis across the Roku Platform 

• Providing feedback directly to leadership on performance of various initiatives and untapped opportunities 

We're excited if you have 

• 4+ years of work experience with a bachelor's degree or master's degree in quantitative field (e.g., Statistics, Business Analytics, Data Science, Mathematics, Economics, Engineering or Computer Science) 

• 4+ years of experience in product analytics. Experience with platforms in the media and entertainment industry preferred 

• Expertise in SQL, SAS, R, Python or other programming language to query data and perform analysis 

• Demonstrated ability to influence quantitatively meaningful business outcomes 

• Hands on experience with visualization tools like Tableau or Looker 

• Have a bias towards action in resolving issues and operate in a high-energy, fast-paced environment 

• Hands on experience in A/B testing and statistical modeling/forecasting 

This role can be based in either Cambridge, or Manchester. You are required to work in the office for 4 days per week, this is the core requirement of the role

#LI-ST1

About the role 

Roku is looking for a Sr. Data scientist to join the Core Analytics team supporting our Viewer Product team. In this role, you will leverage data analytics to support and improve our Live product. You will own end-to-end analytics that shape how viewers discover, engage with, and return to Live experiences on Roku. You will work closely with product management and engineering to identify opportunities to create new features, drive their adoption, and generate value for Roku. This individual will investigate and develop solutions to track, monitor and improve our ecosystem. The successful candidate is quantitatively driven, detail-focused, and possesses an elevated level of problem-solving expertise. 

What you'll be doing 

• Analyze structured and unstructured data and communicate insights to help stakeholders solve business problems, identify trends and make data-driven decisions 

• Advise on key product development strategy decisions to drive our Live product experience 

• Develop and maintain dashboards, reports, and data visualizations to monitor key metrics for operational and systems health 

• Develop necessary data pipelines to power automation, validation and reporting 

• Collaborate with stakeholders to align data science initiatives with organizational goals and strategy design and execute A/B tests 

• Perform exploratory data analysis on emerging trends and execute advanced analysis across the Roku Platform 

• Providing feedback directly to leadership on performance of various initiatives and untapped opportunities 

We're excited if you have 

• 4+ years of work experience with a bachelor's degree or master's degree in quantitative field (e.g., Statistics, Business Analytics, Data Science, Mathematics, Economics, Engineering or Computer Science) 

• 4+ years of experience in product analytics. Experience with platforms in the media and entertainment industry preferred 

• Expertise in SQL, SAS, R, Python or other programming language to query data and perform analysis 

• Demonstrated ability to influence quantitatively meaningful business outcomes 

• Hands on experience with visualization tools like Tableau or Looker 

• Have a bias towards action in resolving issues and operate in a high-energy, fast-paced environment 

• Hands on experience in A/B testing and statistical modeling/forecasting 

This role can be based in either Cambridge, or Manchester. You are required to work in the office for 4 days per week, this is the core requirement of the role

#LI-ST1

About the Team

The Advanced Development team at Roku pushes beyond today’s product lines to invent the next generation of intelligent and generative media systems.
We explore ideas that sit years ahead of production, developing foundational technologies that will redefine how content is understood, created, and personalised across millions of Roku devices.

This is a rare environment — a PhD-level, cross-disciplinary group combining machine learning research, software engineering, and DevOps.
Everyone here is an expert, but not narrowly focused. The team blends deep technical mastery with broad creative vision — people who challenge convention, embrace ambiguity, and build what’s never been built before. It’s a collaborative, low-ego, ownership-driven culture built on trust and curiosity.

We’re seeking an Applied Scientist with a strong foundation in mathematics, machine learning, and computer science, combined with experience in cloud engineering, DevOps, and computer vision — someone who thrives where research meets production.

About the Role

As a Senior Applied Machine Learning Engineer, you’ll help design, build, and deploy the systems that make media smarter.
You’ll work across the full model and software lifecycle, from prototype to production, developing scalable ML pipelines and cloud architectures that power generative AI, intelligent media understanding, content analysis, and advertising intelligence.

You’ll operate at the intersection of machine learning, infrastructure, and software engineering, taking ownership from data collection through deployment — and seeing your work directly influence how audiences experience Roku’s content and advertising ecosystem.

What You’ll Be Doing

• Deploying scalable, fault-tolerant computer vision, media understanding, and generative AI systems to production

• Overseeing the full model development cycle: ideation, prototyping, implementation, deployment, testing, and operations

• Designing uncertainty metrics and communicating results to both technical and non-technical stakeholders

• Gathering and compiling datasets, defining annotation ontologies, auditing annotation operations, and ensuring data quality

• Staying up to date with industry and academic trends in computer vision, machine learning, and generative models for media and advertising

• Working closely with product and other engineering teams to implement new content and advertising experiences through cloud services

• Integrating services from other teams around the company, while also providing reusable ML services to others

• Evaluating and providing feedback on new platform technologies provided by internal teams

• Working with QA teams to address bugs and contribute to automation and quality assurance

We’re Excited If You Have

• A Master’s degree (PhD preferred) in Computer Science, Applied Mathematics, or a related field

• Strong background developing applied machine learning systems using PyTorch or TensorFlow

• Expertise in image processing, computer vision, or natural language processing

• Experience using AWS, GCP, or Azure for storing data, training, and serving models

• Proven ability to evaluate models and communicate insights effectively

• Experience building APIs with frameworks such as GraphQL or REST

• Experience with workflow orchestration tools such as Airflow, Argo, AWS Step Functions, or Metaflow

• Hands-on experience with Docker, Kubernetes, Terraform, CloudFormation, CI/CD automation, and Python build or packaging tools

#LI-PA1

Your Impact at LILA

Lila Sciences is seeking Platform Scientists, Soft Materials Focus to ideate, prototype, and transfer new experimental concepts for AI Science Factories targeting complex and soft material systems. In this role, you will work at the forefront of scientific ideation—partnering with a broad range of chemistry, materials, and AI teams to define new approaches to formulation, structure–property relationships, and performance evaluation. You will translate these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research.

What You'll Be Building

• Collaborate with diverse scientific teams to ideate new experimental strategies for soft and complex materials, including formulations, colloids, polymers, gels, and biological or hybrid systems
• Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays
• Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts
• Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales
• Transfer successful prototypes into production-ready systems within Lila’s AI Science Factory platform, enabling autonomous experimentation

What You’ll Need to Succeed

• MS or PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field, with a focus on soft or complex materials
• Demonstrated experience collaborating across scientific disciplines to generate and refine experimental concepts
• Hands-on experience with one or more of the following: SAXS, SANS, rheology, formulation performance or functional assays
• Experience designing and implementing custom experimental workflows and/or scientific software
• Strong programming skills (e.g., Python, C++, or similar) applied to data analysis, automation, or experiment control
• Excellent communication skills and comfort operating in a fast-paced, exploratory R&D environment

Bonus Points For

• Experience with lab automation, high-throughput experimentation, or instrument control software
• Background in formulation science (e.g., consumer products, coatings, energy materials, bio-soft matter)
• Experience linking scattering, rheological, and performance data to predictive or ML-driven models
• Familiarity with prototyping tools such as 3D printing, machining, microfluidics, or custom sample environments
• Industry or national lab experience working on soft materials or complex fluids

Your Impact at LILA

As a Machine Learning Scientist focused on Scientific Reasoning, you will help pioneer the next generation of AI systems capable of reasoning like a scientist. You’ll design novel frameworks that push the boundaries of LLM-based reasoning methods — while also implementing scalable frameworks that integrate with Lila’s platforms. This role bridges deep theoretical thinking with practical ML engineering, enabling breakthroughs in how scientific hypotheses are generated, tested, deployed and optimized.

What You'll Be Building

• Design and formalize frameworks for scientific reasoning with LLMs, including structured prompting, reasoning chains, and test-time compute.
• Explore and implement methods for in-context learning, self-reflection, and adaptive reasoning in scientific discovery workflows.
• Build scalable model prototypes that can be deployed to solve frontier scientific problems.
• Collaborate with scientists and engineers to encode domain knowledge into reasoning systems that integrate symbolic and statistical approaches.

What You’ll Need to Succeed

• PhD (preferred) or equivalent research/industry experience in Computer Science, Machine Learning, AI, Engineering, Materials Science or related fields.
• Strong programming skills in Python with deep expertise in LLM frameworks (PyTorch, HuggingFace Transformers, LangChain, LlamaIndex, and related toolkits).
• Expertise in LLM reasoning methods: in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning.
• Ability to balance theoretical research with practical ML engineering to deliver scalable solutions.

Bonus Points For

• Research experience in causal reasoning, symbolic AI, or probabilistic programming.
• Contributions to open-source LLM reasoning frameworks.
• Familiarity with scientific discovery pipelines in chemistry, biology, or materials science.
• Experience with multimodal reasoning (e.g., combining text, image, and experimental data).
• Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL).

COMPANY DESCRIPTION

Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health, sustainability and beyond exponentially accelerate scientific progress in areas ranging from disease detection and treatment and nature-positive agriculture to novel applications of AI that are driving the creation of new technologies.   

What sets Flagship apart is our ability to advance science and technology by uniting innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet.   

Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. 

THE ROLE

We are seeking a Senior Machine Learning Scientist, Climate and Hydrology to lead the scientific direction and machine learning development for hydrology-aware climate modeling within our broader environmental modeling platform.

This role sits at the intersection of hydrology, weather and climate science, and large-scale machine learning. The Sr. Scientist will help shape how hydrologic process understanding, climate data, and modern ML methods are brought together in next-generation prediction systems, with emphasis on scientifically grounded model development and evaluation.

The individual in this role will work across science, ML, engineering, and data teams to define research priorities, guide model training and benchmarking, build reproducible workflows, and translate scientific insight into scalable model development. This is a cross-functional role requiring strong technical depth, structured scientific thinking, and the ability to move between foundational research and applied execution.

KEY RESPONSIBILITIES

• Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning.
• Help define research priorities, modeling directions, and evaluation strategies for next-generation climate and environmental prediction systems.
• Contribute to the development and improvement of ML-based modeling approaches informed by physical and Earth system science.
• Work with large-scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis.
• Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation.
• Collaborate closely with research, engineering, and data teams to translate scientific goals into scalable technical execution.
• Guide assessment of model performance, uncertainty, and scientific robustness across a range of environmental conditions and applications.
• Communicate findings through internal reviews, external collaborations, publications, and technical presentations.
• Help shape the broader scientific roadmap and contribute to team growth and cross-functional leadership.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• PhD in machine learning, computational science, Earth science, atmospheric science, hydrology, AI, computer science, or a related quantitative discipline.
• 5+ years of postdoctoral, industry, or applied research experience in climate ML, weather ML, hydrologic modeling, Earth system modeling, or a closely related field.
• Demonstrated experience with ML-accelerated weather, climate, or hydrology models, with a strong publication track record in the area.
• Experience working with large climate datasets, including reanalysis products, remote sensing datasets, observational datasets, and model output.
• Experience with the computational infrastructure required to manage, preprocess, and train on large-scale climate datasets, preferably in the AWS ecosystem.
• Strong programming skills in Python and experience with modern ML frameworks such as PyTorch
• Background in scientific ML, spatiotemporal modeling, data assimilation, hybrid physics-ML methods, or related approaches is strongly preferred.
• Ability to design rigorous evaluation frameworks, performance metrics, and benchmarking approaches for environmental prediction systems.
• Strong technical writing and communication skills, including reports, presentations, and peer-reviewed publications.
• Demonstrated ability to work independently in fast-paced, ambiguous environments while collaborating effectively across disciplines.
• Experience leading cross-functional scientific efforts, mentoring researchers, or helping define research roadmaps is preferred.

LOCATION: Cambridge, MA or Boulder, CO (some travel to Cambridge, MA based headquarters if working from Colorado)

ABOUT FLAGSHIP PIONEERING:

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

#LI-TL1

The salary ranges for this role are $127,000 - $205,900 (Colorado) and $168,000 - $231,000 (Massachusetts). Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Protocos currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Protoco's good faith estimate as of the date of publication and may be modified in the future.

What You Will Contribute To Altos

An exciting opportunity is available for a Scientist II to join the Larrieu group at Altos Labs, Cambridge Institute of Science (Cambridge, UK). At Altos, the Larrieu lab is exploring both fundamental questions and translational opportunities. We are seeking a very highly motivated, versatile, creative, and collaborative individual, who is passionate and dedicated about employing their expertise to unravel the deep biology of cell health and resilience. This includes the elucidation of the mechanism of action of specific interventions that can reverse, halt or mitigate the effects of ageing on cell health. 

Responsibilities

• Elucidate processes that contribute to the age-related erosion of cell/tissue resilience.
• Engage in ground-breaking and innovative science and in Altos scientific activities.
• Develop project-specific experimental strategies, techniques, and procedures including new assays and pipelines to support translational projects.
• Lead, design and execute in vitro and in vivo experiments for identification and validation of targets with therapeutic potential
• Develop and implement biochemical and cellular assays to support screening and characterization of potential candidate therapies
• Collaborate widely across Altos to multiply efforts, gain insight into the centrality of the nuclear envelope in ageing and identify potential new therapeutic avenues          
• Collaborate with multidisciplinary teams including chemists, pharmacologists, and bioinformaticians to advance drug discovery projects.
• Present data to a variety of audiences including senior executives through entry-level employees.

Who You Are

Minimum Qualifications

• PhD in life sciences with 3-5 years of relevant postdoc/industry experience
• Extensive experience in mammalian cell culture (including primary cells).
• Strong background in molecular and cell biology with experience in assay development and validation, to support pre-clinical studies.
• Experience in small rodent handling, with an ability to independently design and coordinate the execution of complex in vivo studies, including drug administration, tissue harvest and processing.
• Strong sense of collective ownership of projects within the group and Altos.
• Critical, visionary, and creative thinking with an ability to formulate scientific questions, design strategies, and implement plans effectively.
• Strong organizational skills to manage multiple tasks simultaneously, prioritize workloads, and meet deadlines.
• High level of rigor and precision in experimental procedures, data recording, and documentation.
• Problem-solving skills to identify potential issues, test, and develop innovative solutions.
• Excellent writing and communication skills
• Ability to maintain cooperative working relationships with a broad range of people, including staff colleagues, lab members and the community

Preferred Qualifications 

• Understanding of in vivo delivery systems such as AAV, LNP, lentivirus etc.
• Biochemistry skills, including biochemical and enzymatic assay development
• Some proficiency in R and Python to support data analysis
• Prior industry experience

The salary range for Cambridge, UK:

• Scientist II, Biological Sciences: £61,400 - £80,800

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. As such, we’re looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research.

We are looking for researchers with experience of AI in low-power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality. We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real-time computer vision, generating and reasoning over audio/video streams.

The Team

Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences (NeurIPS, ICML, ICLR) as well as specialist workshops, and collaborate with other research teams and organisations across the world.

We pride ourselves on being a supportive and collaborative team, where we organise around our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence- and graph-based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.

Perhaps the best way to get an idea of what we’re all about is to read one of our papers or an article on our blog. If you’re excited to work at the cutting edge of AI supported by new hardware and want to develop your skills in this area, we’d love to hear from you!

Responsibilities and Duties

• Generate AI/ML ideas, design experiments, implement them & evaluate results.
• Prepare, submit & present your work to AI conferences and workshops.
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.

About you:

Essential:

• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
• Experience in embodied AI, world models or robotics.
• Python programming in a modern deep learning framework, e.g. PyTorch or JAX.
• Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
• Capable of designing, executing and reporting from ML experiments.
• Mathematics skills to support the above: calculus, probability theory and linear algebra.
• Experience submitting papers to international scientific conferences or workshops.

Desirable:

• Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton.
• Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling.
• Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution.
• Conference or workshop submissions in the fields of embodied AI, world models, or robotics.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

MORSE is searching for a Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Perform data analysis, test and evaluation of existing machine learning algorithms, and development of advanced algorithms to model physical and autonomous systems,

• Work with MORSE’s current team of engineers to transition algorithms to software applications and real-time embedded systems.

• Support the transition of the developed algorithms to software using one or more programming languages such as Python, C, C++, Java, or MATLAB.

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Research and identify new methods for machine learning and data analysis

Requirements:

• US CITIZENSHIP REQUIRED and an active Top Secret Security Clearance with SCI eligibility 

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 3+ years of experience in Data Science or Analysis

• Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods

• Proficiency in one or more programming languages like Python, Matlab, C, or C++

• Demonstrated experience with large, multidimensional, or complex data sets in one or more of the following areas: parsing, cleaning, storage strategies, provenance tracking, database formats, and parallelized data transformations

• Good communication skills

• Self-starter and driven

• Prior experience in defense is a plus

MORSE is searching for an experienced Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Perform data analysis, test and evaluation of existing machine learning algorithms, and development of advanced algorithms to model physical and autonomous systems,

• Work with MORSE’s current team of engineers to transition algorithms to software applications and real-time embedded systems.

• Support the transition of the developed algorithms to software using one or more programming languages such as Python, C, C++, Java, or MATLAB.

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Research and identify new methods for machine learning and data analysis

Requirements:

• US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 5+ years of experience in Data Science or Analysis

• Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods

• Proficiency in one or more programming languages like Python, Matlab, C, or C++

• Demonstrated experience with large, multidimensional, or complex data sets in one or more of the following areas: parsing, cleaning, storage strategies, provenance tracking, database formats, and parallelized data transformations

• Good communication skills

• Self-starter and driven

• Prior experience in defense is a plus

MORSE is searching for a Lead Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will lead teams and strategy for Algorithm Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Define goals and expectations for algorithm T&E performance

• Research artificial intelligence data splitting, metrics, and T&E methodology

• Lead strategy and coordination with algorithm development vendors

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Work with MORSE’s current team of engineers and scientists to transition algorithms to software applications and real-time embedded systems.

Requirements:

• US CITIZENSHIP REQUIRED and an Active Top Secret U.S. Security Clearance with SCI eligibility (TS/SCI) 

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 7+ years of experience in Data Science, Artificial Intelligence, or Machine Learning

• Expertise in artificial intelligence, machine learning, and data science 

• Experience in algorithm development and testing

• Excellent communication and presentation skills

• Self-starter and driven

• Ability to be onsite 4-5 days/week 

About the Role:

Stylus Medicine is seeking a highly motivated and collaborative Senior Scientist to join our in vivo Pharmacology team. This role will be responsible for leading NHP studies, including working closely with CROs to manage studies, contribute to protocol writing and design, obtain, quality control, analyze and interpret data, lead investigative technical troubleshooting, ensure consistency in execution across studies, and create detailed and thorough study summaries. Reporting to the Director of in vivo Pharmacology and working closely with cross-functional teams, this is a unique opportunity to contribute to foundational development in a fast-paced, cutting-edge biotech environment and advance the development of transformative in vivo genetic medicines.

Key Responsibilities & Accountabilities: 

• Design NHP study protocols and lead CRO communication
• Analyze, interpret, and communicate NHP study data, including flow cytometry analysis, cytokine analysis and other ex vivo readouts, to inform project direction and decision-making
• Evaluate data for consistency and follow-up as needed, working closely with CROs to optimize study protocols
• Investigate and interpret biological findings from NHP studies
• Manage NHP study test article generation and transfer in collaboration with internal cross-functional teams
• Conduct experiments to optimize protocols for CRO transfer or investigate biological findings
• Generate and manage study documentation, including protocols and study reports
• Effectively communicate findings to internal teams.
• Maintain detailed and accurate laboratory records in compliance with data integrity and documentation standards
• Limited travel may be required

 Qualifications & Skills:

• PhD in Pharmacology, Immunology, Immuno-oncology, or a related field with 4-6 years of relevant industry or academic experience, or a Master's degree with 8+ years of experience
• Demonstrated experience with ex vivo analytical techniques, such as flow cytometry, cytokine analysis, and ddPCR
• Demonstrated ability to design, execute, interpret, and troubleshoot immunology-related in vivo studies and to coordinate the activities of multiple study contributors
• Experience coordinating with animal vendors, CROs or external collaborators
• Prior experience with NHP studies is preferred
• Experience in designing experiments to address PK/PD/biodistribution/tox relationships is a plus
• Experience with LNP or CART delivery technologies and genetic medicine platforms is a plus
• Experience with T cell or PBMC isolation and handling from peripheral blood, engineering, and downstream immunological or molecular assays
• Demonstrated ability to work independently in a laboratory setting, learn new techniques, multitask effectively, and maintain meticulous records
• Demonstrated proficiency in documenting and maintaining an organized lab notebook, lab inventory, and experimental results
• Excellent organizational and communication skills, with a team-first mindset and the ability to convey technical information
• Analytical thinker with the ability to distill complex data into clear, actionable insights

Pay Range: $160,000 - $175,000

Your impact at LILA

We’re building a talent-dense, high-agency research team to develop the next generation of learning systems and reasoning algorithms for agentic LLMs. Our work sits at the intersection of large language models, post-training, and scientific reasoning, with the goal of enabling systems that learn from experience, reason effectively, and improve through interaction.

Scientific domains present a distinct set of challenges that make this problem uniquely hard. Feedback is sparse and delayed — experiments take days or weeks, not milliseconds. Ground truth is expensive or contested. Distribution shift is structural, as instruments, techniques, and knowledge bases evolve continuously. The hypothesis space is vast and reward signal is thin. Existing benchmark do not capture these nuances. The goal is to build systems that can operate effectively in this scientific regime.

This role spans a few complementary directions. Candidates are expected to bring deep expertise in one (ore more) of the following areas. In the event of cross-track expertise, please select the one you align to the most. Our interview process will be catered to verifying the chosen expertise area.

Expertise Area 1 — Agentic system building

Focus: Build systems that autonomously propose, execute, and verify scientific hypotheses over long time horizons.

• Create and analyze long-running auto-research systems that propose and verify hypotheses
• Design planning frameworks for agentic systems operating over long, sparse feedback loops
• Design memory architectures that allow agents to build and retrieve structured knowledge over time
• Explore algorithms in recursive self-improvement, multi-agent coordination, and continual learning

Expertise Area 2: Distillation

Focus: Translate strong inference-time behaviors and reasoning traces into efficient, trainable models.

• Develop distillation strategies from large or ensemble models into deployable systems
• Research methods for self-improvement, including iterative self-distillation and critique loops
• Investigate how to preserve generalization and reduce catastrophic forgetting through the distillation process

Expertise Area 3 — Scalable experience generation

Focus: Develop inference-time algorithms and synthetic data pipelines that generate high-quality training signal for scientific reasoning.

• Design and benchmark inference-time search, sampling, and verification strategies
• Propose new techniques in synthetic environment creation and curriculum learning
• Develop synthetic data generation strategies that capture high-quality scientific reasoning for agentic model training
• Measure the end-to-end impact of inference-time improvements on real scientific tasks

What you’ll need to succeed:

• An advanced degree in computer science, machine learning, or a related field, or or comparable experience
• Strong foundation in LLMs and empirical research
• Experience designing and executing rigorous ML experiments, including benchmarking and ablations
• Experience working with large-scale training or evaluation pipelines
• Ability to define and pursue research directions in open-ended, rapidly evolving spaces
• Strong collaboration and communication skills across research and engineering teams

Bonus points for:

• Experience with synthetic data generation, distillation, or self-improvement loops
• Familiarity with reinforcement learning (e.g., RLHF, on-policy methods)
• Experience with planning, search, or decision-making systems at scale
• Experience in building agentic systems with tool use, or multi-agent workflows
• Background in program synthesis, coding benchmarks, or long-horizon tasks
• Experience building evaluation frameworks or large-scale benchmarks

Scientific rigor & persistence:

• You take a principled approach to experimentation, with careful baselines, ablations, and evaluation design
• You are motivated by understanding why systems work, not just improving metrics
• You prioritize clarity, reproducibility, and intellectual honesty in research
• You are comfortable working through long, nonlinear iteration cycles
• You operate effectively in ambiguous, fast-evolving research environments

The Principal Data Scientist is a senior individual contributor and technical leader on the Customer Analytics team. This role leads the development and delivery of customer-facing analytics and data science solutions, with a focus on scientific rigor, scalable implementation, and measurable business impact. 

The position partners closely with Customer Solutions, Data Engineering, and Customer Success to translate complex business challenges into production-grade analytics, machine learning, and AI capabilities that improve product outcomes and client value. 

CMT is looking for a Principal Data Scientist I, Customer Analytics to help us change the world. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Serve as a technical lead with a deep understanding of modeling methods from underlying mathematics, to assumptions, tradeoffs, interpretability, and limitations to ensure results are robust and reliable. 
• Use independent judgment and discretion to frame ambiguous business and customer problems into well-defined data science problem statements, project plans, modeling approaches, and measurable success metrics 
• Develop and implement advanced statistical and machine learning models end-to-end, including data pipelines, feature engineering, model development, validation, deployment, and ongoing monitoring
• Partner with analysts to build reporting dashboards and data products that convert model outputs into clear, actionable insights for internal stakeholders and external clients 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in a related field 
• 7+ years of working experience in data science, machine learning, advanced analytics or AI-focused roles 
• Deep foundation in statistics, experimental design, and causal inference, including the ability to explain methodology choices and validate assumptions 
• Demonstrated experience deploying and maintaining models or analytical systems in production using CI/CD practices, including monitoring and performance management 
• Strong data science language in Python (required) and SQL 
• Familiarity with Databricks, MLflow, Spark, or similar modern data/ML platforms

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and annual performance bonus
• Equity may be awarded in the form of Restricted Stock Units (RSUs)
• Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $153,800 to $192,300. This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

The Opportunity:

Relay Therapeutics is seeking a highly motivated Scientist to join our Drug Discovery team in a unique hybrid role that integrates synthetic chemistry with cheminformatics. This position is ideal for a scientist who enjoys working at the interface of experimental and computational disciplines and is excited to help shape how data-driven chemistry is done in a modern biotech environment.

Your Role:

• Maintain and support tools used in compound registration, lab operations and data ingestion from assays, as well as broader data and software access workflows
• Design and execute synthetic chemistry workflows, with a focus on high-throughput or parallel synthesis to support medicinal chemistry programs
• Contribute to the design, enumeration, and prioritization of compound libraries using cheminformatics tools
• Collaborate closely with computational chemists, data scientists, and medicinal chemists to guide compound design using data-driven insights
• Analyze and interpret experimental data to inform structure–activity relationships (SAR) and compound optimization
• Help develop and refine internal workflows that integrate synthetic chemistry with computational approaches
• Maintain clear documentation and communicate results effectively across multidisciplinary teams

Your Background:

• Ph.D. or M.S. in Organic Chemistry or a related field, with 2–5 years of relevant industry experience preferred
• Demonstrated experience in synthetic organic chemistry
• Familiarity with cheminformatics tools and concepts (e.g., molecular representations, library design, property prediction)
• Experience with scripting or data analysis tools (e.g., Python, RDKit)
• Strong problem-solving skills and the ability to work both independently and collaboratively
• Excellent communication skills and a desire to work in a highly cross-functional environment

What We’re Looking For

• A scientist who enjoys bridging “hands-on” chemistry with computational thinking
• Someone comfortable working in a fast-paced, evolving biotech setting
• A candidate who is curious, adaptable, and interested in shaping new ways of integrating chemistry and data science

Estimated Salary Range: [$88,000-$126,000].

The range provided above is based on what we believe to be a reasonable estimate for this job at the time of posting. Actual base salary will depend on a number of factors, including but not limited to, a candidate’s education, experience, skills and location.

#BP1

Company Overview:

PhaseV (HQ in Boston, R&D in Tel Aviv) is a cutting-edge startup, pushing innovation in the drug development process to bring new treatments to more patients, in a more efficient and precise way. Leveraging the power of advanced causal inference and pushing the boundaries of machine learning, PhaseV detects hidden signals in clinical data and extracts actionable insights for planning the optimal trial. The company's proprietary ML-based platform for adaptive clinical trial design and closed-loop execution enables sponsors to easily and quickly unlock the potential of adaptive clinical trials, reveal the optimal adaptive design to meet their trial objectives and execute more efficient, more precise, and more successful clinical trials. Collaborating with 7 of the top pharmaceutical companies, as well as multiple CROs and biotechs, we are poised to make a significant impact on how drugs are developed and brought to market.

Position Overview:

We are seeking a talented Data Scientist to join our team of researchers. The ideal candidate will have a strong foundation in machine learning and statistics with an interest in causal inference. A couple of recent preprints we’ve released to get a sense of the challenges:

• Causal Responder Detection (https://arxiv.org/abs/2406.17571)
• Robust CATE Estimation Using Novel Ensemble Methods. (https://arxiv.org/abs/2407.03690)

Key Responsibilities:

Technical Development:

• Implement and optimize ML algorithms, with a focus on causal ML applications in clinical trials
• Collaborate with senior data scientists to develop and improve our analytical platforms
• Work alongside clinical and biological experts to translate complex problems into technical solutions

Research & Analysis:

• Conduct rigorous statistical analyses of both randomized and observational data
• Develop and validate methods for responder identification and treatment effect estimation
• Document and present methodologies and results for internal and external stakeholders

Collaboration:

• Work cross-functionally with engineering and product teams
• Contribute to technical discussions and peer code reviews
• Support the preparation of technical documentation and research papers

Qualifications:

Education:

• Master's in Computer Science, Statistics, Data Science, Engineering or a related field
• Ph.D. is an advantage but not required

Experience:

• 3+ years of experience in data science or machine learning roles
• Experience with ML in a practical research or industry setting
• Background in statistical modeling and analysis

Skills:

• Strong programming skills in Python (R in addition - an advantage)
• Proficiency in statistical analysis and machine learning
• Experience with data visualization and communication of technical concepts
• Strong analytical and problem-solving skills

Preferred:

• Familiarity with causal inference concepts
• Experience in healthcare or biotech industry
• Experience with large-scale data processing

What We Offer:

• Join us on a mission to bring more effective drugs to more patients.
• The opportunity to work with an amazing team passionate about making a real-world impact.
• Extremely hard and diverse problem setting, in which the team is pushing the envelope.
• A collaborative and dynamic startup environment.
• Professional growth and development opportunities.

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You’ll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

• Pioneering approaches for precise and dexterous robotic manipulation that leverage foundation models, reinforcement learning, diffusion-based methods, and human guidance to enable adaptive and intelligent robotic systems capable of complex tasks across diverse scientific environments
• Developing novel human-robot interaction frameworks that incorporate imitation learning, and learning from human guidance, feedback, demonstrations and corrections, creating intelligent robotic agents that can seamlessly integrate with human scientific workflows and rapidly adapt to new experimental contexts
• Advancing dexterous manipulation research through cutting-edge machine learning approaches, including diffusion models and adaptive learning algorithms, that synthesize multi-modal sensing (tactile, visual, and language) to develop generative skill representation sand sophisticated motor learning policies for intelligent robotic systems
• Designing autonomous robotic systems with trust calibration mechanisms, enabling intelligent agents that can dynamically adjust their behaviors based on contextual information in complex scientific tasks

What You’ll Need to Succeed

• Ph.D. in Robotics, Machine Learning, Computer Science, or a related field with demonstrated expertise in foundation models for robotic learning
• Advanced proficiency in reinforcement learning, diffusion-based methods, imitation learning, and adaptive learning algorithms for robotic manipulation
• Expert-level experience with machine learning frameworks (PyTorch, TensorFlow) and deep learning architectures for developing foundation models, with specific expertise in diffusion-based generative models for robotics
• Proven track record of developing multi-modal perception systems integrating tactile, visual, language and other contextual sensing for intelligent robotic agents
• Strong publication record in robot learning, demonstrating innovative approaches to trust calibration, contextual learning, and generative robotic skill learning

Bonus Points For

• Research contributions to foundation models and diffusion methods in robotics
• Experience with large-scale machine learning model development, particularly generative and diffusion-based approaches
• Expertise in human-in-the-loop learning, correction-based training paradigms, and diffusion-guided skill transfer
• Demonstrated ability to translate theoretical machine learning research, especially diffusion and generative models, into practical robotic implementations

Your Impact at LILA

Join us in shaping the future of science! We are seeking Sr Principal, and Principal Software Engineers with full stack experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You'll Need To Succeed  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

Join us in shaping the future of science! We are seeking Staff, Senior II, and Senior I Software Engineers with either frontend or backend experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5-10 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

The Role:

Reporting to the Head of PV Science, the Associate Director, Drug Safety and Pharmacovigilance Scientist is responsible for assessing and interpreting safety data from multiple sources, including clinical trials, spontaneous and solicited reports, aggregate, and literature reports. This individual is expected to provide interpretation and summaries of drug safety information and provide input in the generation of safety reports (e.g., DSURs, PADERs, PBRERs, and clinical safety assessments). This individual may also support the medical assessment of Individual Case Safety Reports (ICSRs) and other drug safety information. The individual will be an integral part of a group of safety professionals within Nuvalent and will closely collaborate with safety teams in Contract Research Organizations (CROs) and partners. He/she will need to maintain medical knowledge as required by the role, strong and current knowledge of drug safety and pharmacovigilance regulations, pharmacovigilance practices, safety surveillance and risk-management practices.

Responsibilities:

• Contribute to the generation of aggregate safety reports including development safety update reports, periodic benefit risk evaluation reports, and provide medical input in review of new or existing safety documents to ensure compliance with relevant regulatory requirements, such as protocols, safety summaries and regulatory reports
• Contribute to signaling and safety surveillance processes, including the identification of safety observations, emergent safety concerns and new safety signals, ensure prompt assessment and communication of confirmed safety signals
• Serve as a medical resource for the generation and review of clinical trial protocols, informed consent forms (ICFs) and investigator brochures (IBs) and the development of Reference Safety Information
• Contribute to creation or and updates to Risk Management Plans (RMPs) and/or Risk Evaluation and Mitigation Strategies (REMS) and the maintenance of these documents
• Contribute to the development of Standard Operating Procedures, Working Instructions and other guidance documents
• Provide safety and pharmacovigilance training programs as required
• Collaborate cross functionally (e.g., Reg Affairs, Clin Ops, Clin Science) to ensure pharmacovigilance input
• Support the medical assessment of ICSRs as needed
• Support other pharmacovigilance and drug safety responsibilities as assigned

Competencies Include:

• Design global risk management frameworks for Nuvalent’s medicines
• Translate safety data into clinical insights
• Adapt visualization tools for safety surveillance
• Influence multidisciplinary teams to prioritize patient safety.
• Strong ability to build relationships, collaborate and influence across disciplines within Nuvalent and with outside stakeholders

Qualifications:

• 4+ years’ experience in Drug Safety / Pharmacovigilance in a pharmaceutical or biotech company, CRO or regulatory agency
• 7+ years of Pharma / CRO experience. 
• Degree in a medical or healthcare related discipline like MD, PharmD, RN or PhD.
• Excellent knowledge of US and EU drug safety regulations, CIOMS and ICH guidelines
• Experience with medical drug safety assessments, drug safety surveillance and monitoring activities
• Experience with safety data collection and interpretation from clinical trials, literature and post market
• Experience with preparation of responses to Regulatory Authorities and experience with IND/NDA submissions and negotiations with Regulatory Authorities as part of marketing approval
• Experience with the development and updates to Reference Safety Information, IB, Company Core Data Sheet and local labels
• Excellent verbal, written and presentation skills

Additional Information:

Nuvalent is committed to fair and equitable compensation practices, aiming to provide employees with competitive total rewards packages.

The targeted salary range reflects what Nuvalent reasonably and in good faith expects to offer for this position at the time of posting, but the final salary determination may be within or outside this range based on various factors, including, but not limited to, experience, skills, education, and market factors.  The range will be reviewed regularly and is subject to change.

Nuvalent also offers a comprehensive benefit package to support our employees at each stage of their career, financial, health, and well-being journey, including medical, dental, and vision insurance, 401(k) retirement savings plan, generous paid time off (including a summer and winter company shutdown), and much more.

Position Overview

We are seeking a motivated and skilled Senior Scientist to join the Nonclinical Development group, contributing to the DMPK function in support of exploratory and IND-enabling programs across Prime Medicine’s pipeline. Reporting to the Associate Director, DMPK/Bioanalytical Sciences, this individual will independently analyze and interpret datasets from in vivo studies, contribute to nonclinical regulatory documents, and work cross-functionally with pharmacology, translational biology and external CROs, to ensure high-quality DMPK data packages are delivered to support program timelines. The ideal candidate has a strong foundation in in vivo pharmacokinetics for RNA therapeutics and/or LNP-based delivery systems, thrives in a fast-paced and matrixed organization, and possesses the flexibility and positive attitude needed to make meaningful contributions to the Nonclinical Development team.

Primary Responsibilities

• Analyze and interpret PK study data from exploratory and IND-enabling in vivo
• Perform non-compartmental analysis (NCA) using Phoenix WinNonlin to derive key PK parameters (Cmax, AUC, T½, Vd, CL).
• Leverage expertise in DMPK to provide recommendations for in vivo study designs in collaboration with pharmacology and key stakeholders.
• Perform bioanalytical assay development (30%) and collaborate with bioanalytical scientists to trouble-shoot challenges during method development to ensure quantitative methods for key analytes (LNP lipid components, mRNA, pegRNA, PD biomarkers) meet regulatory expectations and data quality standards..
• Contribute to nonclinical regulatory documents including pharmacokinetics summaries and nonclinical study reports under the guidance of senior stakeholders in Nonclinical Development.
• Maintain thorough records in the electronic laboratory notebook (ELN); prepare clear data summaries, presentations, and technical memos for program team and governance meetings.

Qualifications

Minimum Qualifications

• D. in pharmacokinetics, pharmaceutical sciences, pharmacology, biochemistry, or a related discipline.
• 6+ years of cumulative experience. Industry experience (biotech or pharmaceutical) with direct responsibility for in vivo DMPK study design, execution, and interpretation is required; postdoctoral training in a DMPK or translational pharmacology setting is strongly preferred
• Demonstrated experience with in vivo PK studies in preclinical models and proficiency in NCA using Phoenix WinNonlin or equivalent software.
• Familiarity with regulatory expectations for nonclinical DMPK assessments and bioanalytical assay development.
• Demonstrated ability to coordinate with external CROs, including scientific guidance, protocol development, and data review..
• Strong written and verbal communication skills; ability to present complex DMPK data clearly to multidisciplinary audiences.
• Highly self-motivated, collaborative, and organized, with the ability to manage multiple priorities independently in a fast-paced matrix environment.

Preferred Qualifications

• Familiarity with PK/PD modeling concepts; experience with Phoenix WinNonlin modeling modules a plus.
• Experience with LNP-based delivery systems and/or RNA therapeutics (mRNA, siRNA, ASO, sgRNA or related modalities).
• Experience with exploratory DMPK studies, evaluating new delivery vehicles and evaluation of biodistribution using in vivo
• Familiarity with bioanalytical platforms supporting DMPK studies, including LC-MS/MS, RT-qPCR/ddPCR, ELISA/MSD.
• Ability and excitement to contribute to the development and success of the Nonclinical Development team.

Position Overview

We are seeking an enthusiastic, self-motivated Senior Scientist to join the Nonclinical Development group, supporting the nonclinical safety assessment function for IND-enabling programs across Prime Medicine’s pipeline. Reporting to the Associate Director, Safety Assessment, the successful candidate will support the design, execution, and interpretation of nonclinical safety studies conducted both in-house and at CROs, with an initial focus on liver-targeted therapeutics. This role requires hands-on involvement in assay execution and troubleshooting, as well as active participation in study oversight of work being done at CRO and data analysis.

This role requires collaboration within cross-functional teams. The ideal candidate will hold a Ph.D. in toxicology or a related field with 6+ years of pharma/biotech experience in nonclinical safety assessment, or an M.S. in toxicology or a related field with 10+ years of experience in nonclinical safety assessment, the ability to work independently, provide domain expertise and leadership, as well as cross-functionally in a fast-paced, matrixed environment with a positive, flexible attitude.   

Primary Responsibilities

• Contribute to nonclinical safety activities as part of cross-functional Discovery and Development project teams, supporting program progression through IND-enabling stages.
• Design, execute, and troubleshoot nonclinical safety studies, including hands-on laboratory work (~30%) to support assay development, data generation, and issue resolution.
• Support the execution and oversight of nonclinical safety studies (GLP and non-GLP) at CROs, including active involvement in troubleshooting assay and study-related challenges.
• Analyze and interpret study data with guidance and contribute to the preparation of study reports and supporting documents for regulatory submissions.
• Collaborate with Pharmacology, DMPK, and other functions to support exploratory studies (e.g., exploratory toxicology, DMPK, biodistribution, and delivery platform evaluation).
• Contribute to evaluation of new delivery approaches, Lipid and RNA components, and emerging targets to support pipeline expansion.
• Assist in identifying potential safety findings and contribute to discussions on data interpretation and next steps.
• Ensure studies and internal activities are conducted in compliance with regulatory guidelines and internal standards.

Preferred Qualifications

• Ph.D. in toxicology or a related discipline with 6+ years of biopharmaceutical industry experience, or M.S. in toxicology or a related field with 10+ years of relevant biopharmaceutical industry experience supporting drug development in nonclinical safety/toxicology.
• Experience in large molecule therapeutic development, along with a background in immunology, is desirable.
• Understanding of toxicology principles, nonclinical safety evaluation, and the drug development process, with some experience interpreting toxicology data and contributing to technical and scientific reports.
• Demonstrates strong scientific judgment and leadership with the ability to evaluate information, identify potential issues, and propose practical solutions with guidance as needed.
• Highly organized and detail-oriented with strong attention to accuracy and quality.
• Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams and with external partners.
• Experience supporting nonclinical studies at CROs is preferred but not required.

Your Impact at LILA

We are seeking a curious, driven, and collaborative Scientist to join our discovery platform team focused on decoding mRNA translation dynamics. You will develop workflows that utilize next-generation pooled screening strategies like polysome profiling and Ribo-seq to to generate rich biological datasets that feed directly into Lila's machine learning models. This is a unique opportunity to help invent a new approach to biological discovery by integrating synthetic biology, high-throughput experimentation, and intelligent automation.

What You'll Be Building

• Design and execute high-throughput pooled screening campaigns to interrogate mRNA translation dynamics across diverse sequence and structural contexts
• Develop and optimize cell-free and in-cell assay systems for quantitative measurement of translation efficiency, kinetics, and regulation across different cell environments
• Collaborate closely with computational and ML teams to define data requirements, validate model predictions, and close the loop between experiment and prediction
• Establish and refine next-generation library design strategies, leveraging combinatorial and rational approaches to explore sequence space efficiently
• Analyze and interpret complex biological datasets, distilling key findings into actionable insights for platform advancement
• Contribute to the development of automated and semi-automated experimental pipelines to increase throughput and consistency

What You’ll Need to Succeed

• MSc with 4+ years of industry or academic experience, or PhD in a relevant field (molecular biology, bioengineering, synthetic biology, chemical biology, etc.)
• Deep expertise in mRNA biology and translation regulation
• Experience with next-generation sequencing based assays of mRNA translation such as polysome profiling and Ribo-seq
• Strong quantitative and analytical skills with experience handling large-scale biological datasets
• Excellent communication and collaboration skills with a track record of working effectively in interdisciplinary teams

Bonus Points For

• Experience integrating experimental data with machine learning or computational modeling pipelines
• Proficiency in Python, R, or other scripting languages for data analysis and visualization
• Background in generating and screening complex, high-diversity sequence libraries
• Familiarity with laboratory automation, liquid handling systems, or high-throughput workflow development
• Experience with in-situ sequencing of RNA with imaging like STARmap and Ribomap

Your Impact at LILA

The Scientist I/II, Organic Chemistry will develop, execute, and optimize modern chemical transformations that support Discovery Chemistry efforts across Lila’s platform, with a focus on the rapid synthesis of small molecules and structurally diverse chemical matter. This role is intended for an experimental organic chemist who combines strong foundations in synthetic chemistry with hands-on experience in high-throughput experimentation (HTE), reaction workup, and analytical characterization.

Working closely with Discovery Chemistry, analytical chemistry, automation, screening, and AI/computational teams, this scientist will help build and apply efficient chemistry workflows that accelerate molecular design–make–test–analyze cycles. The Scientist II will contribute to reaction development, analog generation, and route execution using modern organic chemistry approaches that are compatible with scalable, data-rich, and increasingly automated discovery environments.

This role is ideal for a chemist excited by solving synthetic problems at the interface of reaction innovation, high-throughput experimentation, process efficiency, and analytical insight, and who is motivated to help shape next-generation discovery workflows beyond traditional bench chemistry.

What You'll Be Building

• Design, execute, and optimize chemical transformations relevant to Discovery Chemistry programs, with emphasis on the rapid synthesis of small molecules and analog series.
• Apply modern synthetic organic chemistry to enable efficient exploration of structurally diverse and medicinally relevant chemical space.
• Plan and perform multi-step synthesis, reaction optimization, workup, purification, and compound characterization in support of molecular discovery campaigns.
• Design and execute HTE workflows for reaction screening, condition optimization, reagent evaluation, and rapid assessment of transformation scope.
• Develop robust approaches for reaction setup, reaction workup, sample preparation, and analytical readout to support fast and information-rich experimentation.
• Use analytical tools such as chromatography, NMR, and related methods to assess reaction performance, characterize products, and guide synthetic decisions.
• Contribute to the development of practical and scalable chemistry workflows that integrate reaction discovery, reaction optimization, and downstream compound generation.
• Partner closely with Discovery Chemistry scientists to translate molecular design concepts into executable synthetic strategies and experimentally tractable reaction plans.
• Collaborate with analytical chemistry and automation teams to build workflows that connect reaction execution with streamlined workup, purification, and data generation.
• Support the adaptation of synthetic workflows to parallel, automated, or robotics-enabled platforms where appropriate.
• Interpret reaction and analytical data rigorously, identify bottlenecks, and propose solutions to improve efficiency, robustness, and reproducibility.

What You’ll Need to Succeed

• PhD in Organic Chemistry, Medicinal Chemistry, or a closely related discipline with relevant postdoctoral and/or industry experience.
• Strong expertise in synthetic organic chemistry, including design and execution of multi-step synthesis and development of chemical transformations relevant to small molecule discovery.
• Hands-on experience with HTE for reaction screening, optimization, or scope evaluation.
• Experience with reaction workup, sample preparation, purification, and analytical characterization in fast-paced synthetic workflows.
• Strong working knowledge of analytical methods commonly used to support organic synthesis.
• Demonstrated ability to troubleshoot challenging reactions and independently solve synthetic and experimental problems.
• Strong understanding of how reaction design, execution, workup, and analysis fit together in efficient discovery workflows.
• Ability to work effectively in interdisciplinary environments spanning chemistry, analytics, automation, and computational sciences.
• Strong organizational, documentation, and communication skills, with commitment to scientific rigor and reproducibility.

Bonus Points For

• Experience supporting Discovery Chemistry or medicinal chemistry programs in biotech, pharma, or advanced research environments.
• Familiarity with modern reaction classes relevant to small molecule discovery, including coupling chemistry, heterocycle synthesis, late-stage functionalization, and rapid analog generation.
• Experience with parallel synthesis or robotics-enabled chemistry workflows.
• Exposure to data-rich, AI-enabled, or platform-based R&D environments.
• Collaborative mindset and enthusiasm for building modern chemistry capabilities that go beyond traditional bench-scale synthesis.

Your Impact at LILA

The Scientist I/II, Process Chemistry will develop and apply modern process chemistry approaches to support Discovery Chemistry efforts across Lila’s platform, with a focus on reaction/reactor engineering, process design, high-throughput experimentation, and digitalized chemistry workflows for small molecules and related molecular matter. This role is intended for a hands-on scientist who combines strong foundations in synthetic and process chemistry with an engineering mindset and experience building practical, scalable, and data-rich experimental workflows.

Working closely with Discovery Chemistry, analytical chemistry, automation, platform engineering, and AI/computational teams, this scientist will design, execute, and optimize reaction and process workflows that improve the speed, robustness, and scalability of chemical transformations. The Scientist I/II will help bridge early discovery chemistry and modern process development by establishing experimentally efficient, digitally enabled, and automation-compatible approaches to reaction screening, process optimization, and chemistry execution.

This role is ideal for a scientist excited by the intersection of chemistry, engineering, high-throughput platforms, process intensification, and digital experimentation, and who wants to help shape next-generation process chemistry capabilities beyond traditional bench development.

What You'll Be Building

• Design, execute, and optimize process-relevant chemical transformations that support Discovery Chemistry programs and the generation of small molecules.
• Develop reaction and process workflows with emphasis on engineering rigor, scalability, reproducibility, throughput, and data quality.
• Apply high-throughput experimentation (HTE) to reaction screening, process optimization, condition scouting, and evaluation of process-relevant variables.
• Build and execute workflows that connect reaction setup, process screening, workup, analytical readout, and data capture into efficient experimental cycles.
• Contribute to the design of digitally enabled process chemistry workflows, including structured experimental data generation, electronic documentation, and integration of chemistry data into computational and AI-ready systems.
• Collaborate with automation and platform teams to develop and adapt reaction and process workflows for robotics-enabled experimentation.
• Work closely with analytical chemistry teams to ensure rapid and informative analytical support for reaction monitoring, impurity assessment, and process decision-making.
• Evaluate reaction performance through both chemistry and engineering lenses, including yield, selectivity, impurity formation, mass balance, robustness, throughput, and operational simplicity.
• Establish best practices for AI-enhanced process design in early discovery settings, balancing speed and molecular access with process understanding and future scalability.
• Stay current with advances in modern process chemistry, reaction engineering, HTE, digitalization, automation, and enabling technologies relevant to next-generation discovery chemistry.

What You’ll Need to Succeed

• PhD in Process Chemistry, Organic Chemistry, Chemical Engineering, Medicinal Chemistry, or a related discipline with relevant postdoctoral and/or industry experience.
• Strong hands-on experience in process chemistry, reaction development, or scale-relevant synthetic chemistry.
• Demonstrated experience applying engineering principles to chemical process design, optimization, and troubleshooting.
• Experience with HTE for reaction or process screening, optimization, and data-rich experimentation.
• Strong understanding of key process variables in discovery chemistry.
• Experience with reaction workup, sample handling, purification, and analytical interpretation in fast-paced chemistry environments.
• Hands-on familiarity with analytical tools commonly used to support process chemistry.
• Experience generating well-structured experimental data to support reproducibility and digital workflows.
• Ability to troubleshoot complex experimental problems and independently drive practical, technically sound solutions.
• Strong collaborative skills and ability to work effectively across chemistry, analytics, automation, engineering, and computational teams.

Bonus Points For

• Experience supporting Discovery Chemistry or small molecule R&D in biotech, pharma, or advanced platform environments.
• Familiarity with modern process chemistry in early discovery settings, including rapid route improvement, robustness assessment, impurity understanding, and scalable reaction design.
• Experience with miniaturized process screening, parallel reactors, or robotics-enabled chemistry platforms.
• Experience contributing to the digitalization of process chemistry, including structured data capture, ELNs, workflow automation, or AI/ML-enabled experimental environments.
• Ability to connect chemistry execution with broader platform goals such as throughput, automation compatibility, and data generation.
• Strong scientific curiosity and enthusiasm for building next-generation process chemistry capabilities that go beyond traditional development paradigms.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs
• Initial proof-of-concept safeguards, such as ML models to detect and block unsafe behavior from scientific AI models, as well as from physical lab outputs.
• Understanding of a range of model capabilities, across primarily scientific but also non-scientific domains (e.g. persuasion, deception) to inform Lila's broader safety strategy.
• Broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.

What You’ll Need to Succeed

• Bachelor's degree in a technical field (e.g., computer science, engineering, machine learning, mathematics, physics, statistics), or related experience.
• Strong programming skills in Python, and experience with ML frameworks (including, for instance, Inspect) for large-scale evaluation and scaffolded testing.
• Experience in building evaluations, or conducting red-teaming exercises, for CBRN / cyber risks (or for frontier model capabilities more generally, including both unsafe and benign capabilities)
• Experience in designing and/or implementing (directly or through consultation) AI safety frameworks for frontier AI companies.
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.

Bonus Points For

• Masters or PhD in a field relevant to safety evaluations of AI models in scientific domains, or a technical field.
• Publications in AI safety / evaluations / model behaviour in top ML / AI conferences (NeurIPS, ICML, ICLR, ACL) or model release system cards.
• Experience researching risks from novel science (e.g. biosecurity, computational biology, etc.) or working with narrow scientific tools (e.g. large scale foundation models for science).

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

Your Impact at LILA

The Senior Scientist, Analytical Chemistry will develop and deploy advanced analytical and characterization strategies to support Discovery Chemistry efforts across Lila’s platform, with a focus on enabling the rapid design, synthesis, screening, and optimization of small molecules and related molecular matter. This scientist will play a key role in generating high-quality, information-rich experimental data that informs chemistry decisions and accelerates platform learning.

Working closely with Discovery Chemistry, automation, AI/computational, and screening teams, this role will establish and scale multimodal characterization workflows that go beyond traditional analytical chemistry approaches. The Senior Scientist will help build an integrated analytical capability spanning compound characterization, reaction monitoring, molecular profiling, and high-throughput data generation to support fast and iterative design–make–test–analyze cycles.

This role will be critical to shaping Lila’s next-generation discovery engine by combining deep expertise in analytical chemistry with high-throughput experimentation, multimodal data generation, AI-enabled workflows.

What You'll Be Building

• Develop, optimize, and implement analytical and multimodal characterization workflows to support Discovery Chemistry programs and molecular discovery campaigns.
• Support the design, synthesis, screening, and optimization of small molecules by delivering rapid, reliable, and information-rich analytical data.
• Lead analytical method development for compound identification, purity assessment, impurity profiling, reaction monitoring, and molecular characterization using techniques such as liquid chromatography, mass spectroscopy, NMR, and complementary orthogonal methods.
• Build characterization strategies that extend beyond traditional analytical methods, incorporating multimodal measurements that provide deeper insight into molecular identity, reaction outcomes, physicochemical properties, and structure–function relationships.
• Partner closely with Discovery Chemistry and screening teams to support high-throughput screening and high-throughput experimentation workflows, including rapid sample analysis, reaction triage, and compound profiling.
• Collaborate with automation and platform teams to integrate analytical instrumentation and data pipelines into robotics-enabled and scalable discovery workflows.
• Work closely with AI and computational teams to ensure analytical datasets are structured, interoperable, and useful for model development, closed-loop learning, and iterative molecule design.
• Establish robust workflows for reaction monitoring, in-process analytics, final compound quality assessment, and characterization of complex mixtures or intermediates.
• Troubleshoot analytical and characterization challenges related to sample preparation, instrumentation, method robustness, data interpretation, and workflow integration.
• Contribute to the development of platform-level capabilities for data-rich molecular discovery, including scalable characterization pipelines, method standardization, and best practices for analytical rigor.

What You’ll Need to Succeed

• PhD in Analytical Chemistry, Organic Chemistry, Pharmaceutical Sciences, Chemical Biology, or a related scientific discipline with 5–8+ years of relevant industry or high-performance research experience.
• Deep expertise in analytical chemistry and molecular characterization in support of chemistry-driven discovery efforts.
• Strong hands-on experience with key analytical techniques for small molecule analysis.
• Demonstrated experience developing analytical methods for compound characterization, reaction monitoring, impurity analysis, and purity assessment.
• Experience supporting Discovery Chemistry, medicinal chemistry, synthetic chemistry, or other molecule-focused R&D environments.
• Strong understanding of how analytical data informs compound progression, screening decisions, reaction optimization, and molecular design.
• Experience working with or supporting high-throughput workflows, including rapid analytical turnaround in fast-paced research settings.
• Ability to solve complex analytical problems independently and work effectively across interdisciplinary teams spanning chemistry, screening, automation, and computational sciences.
• Strong documentation, communication, and data interpretation skills, with a commitment to rigor, reproducibility, and scientific quality.

Bonus Points For

• Experience with multimodal characterization approaches that combine orthogonal measurements to generate deeper insight into molecular systems and discovery workflows.
• Experience supporting high-throughput screening, reaction screening, or automated discovery platforms.
• Familiarity with analytical workflows integrated with robotics, liquid handlers, autosamplers, or other automation-enabled laboratory systems.
• Experience working in AI-enabled or highly data-driven R&D environments where experimental data is used to drive predictive modeling or closed-loop optimization.
• Knowledge of characterization approaches that extend beyond traditional compound QC, including molecular profiling, reaction analytics, and property-focused measurements.
• Familiarity with data systems such as ELNs, LIMS, and software tools used to manage and analyze large analytical datasets.
• Ability to operate effectively in a fast-moving, innovative environment with evolving platform needs and cross-functional priorities.
• Strong scientific curiosity and interest in building next-generation analytical capabilities for molecular discovery.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Set the build and research strategy for Lila’s safety approach to biological / physical risks.
• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Demonstrated ability to set research directions for open problems in dual-use risks in the biological / physical sciences.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

Your Impact at LILA

Lila Sciences is seeking an experienced Senior Research Associate to join our Antibody Platform team. In this role, you will play a pivotal role in building Lila's Scientific Superintelligence platform by leveraging your deep expertise in high-throughput antibody discovery, production, and characterization.

What You'll Be Building

• Design, optimize and execute high-throughput workflows for antibody expression and purification. Drive platform evolution by identifying opportunities to improve efficiency, robustness, and scalability of antibody production.
• Collaborate closely with scientists, engineers, and automation experts to discover, evaluate and implement novel automation tools, technologies, and reagents to expand the Antibody Platform’s capabilities.
• Innovate and adapt protocols to accommodate new antibody formats, targets, and expression strategies.
• Analyze antibody yield and binding characteristics using biolayer interferometry (BLI) and other relevant techniques; interpret and communicate findings effectively.
• Ensure data quality, documentation, and reproducibility in all experiments; actively contribute to knowledge sharing and continuous improvement initiatives. Collaboration, flexibility, and creative problem-solving are key to thrive in this dynamic role.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Biochemistry, Molecular Biology, Bioengineering, or related discipline with 2–5+ years of hands-on industry or academic experience.
• Proficiency with antibody expression in CHO-S, including DNA transfection, small-scale cell culture, and antibody characterization; ExpiCHO expertise strongly preferred.
• Experience using sequence analysis software for molecular biology workflows and annotating antibody sequences, specifically Geneious, Benchling, PipeBio, etc.
• Experience with liquid handling automation and high-throughput formats.
• Experience with biolayer interferometry (BLI) or surface plasmon resonance (SPR) quantitative binding assays, CE-SDS, and antibody developability assays.
• Outstanding troubleshooting skills, adaptability, and ability to drive innovation in experimental design.
• Familiarity with laboratory data analysis, digital recordkeeping, and collaborative scientific workflows.
• Strong communication skills and an eagerness to collaborate with a fast-paced, cross-functional team.

Bonus Points For

• Skilled in cloning, expression and optimization of multispecific antibody formats
• Data analysis using relevant software (Python, R, Spotfire, or similar)
• Scripting for automation platforms

Your Impact at LILA

As a member of our team in the Physical Sciences division, you will design and build intelligent agent-driven systems that enable AI-accelerated and AI-orchestrated process engineering across a broad range of industrial applications. The core mission of this role is to develop methods by which AI agents can reason about, design, simulate, optimize, and operate complex physical and chemical processes using existing or ML-driven process engineering tools. You will focus on creating agentic infrastructures that allow AI systems to plan and execute multi-step process engineering workflows, ranging from process synthesis and flowsheet generation to steady-state and dynamic simulation, control strategy design, and techno-economic evaluation. Your work will directly shape how Lila’s scientific superintelligence performs closed-loop autonomous process engineering to solve real-world problems.

What You'll Be Building

• Architect and implement agentic frameworks that support end-to-end process engineering workflows, including process setup, simulation, optimization, and analysis.
• Develop AI agents capable of autonomously planning, executing, and iterating on process engineering tasks using existing tools (e.g., steady-state and dynamic simulators, optimizers, and data systems).
• Explore agentic approaches for advanced tasks such as process intensification, control co-design, real-time optimization, and closed-loop learning from operational data.
• Improve robustness, interpretability, and reproducibility of agent-driven process engineering workflows; build internal tooling for debugging, observability, validation, and auditability.
• Work with interdisciplinary teams to apply agentic process engineering to a broad range of industrial applications

What You’ll Need to Succeed

• PhD or equivalent experience in Chemical Engineering, Industrial Engineering, Systems Engineering, or a closely related field.
• Research experience in method development for process engineering, a strong publication record in this area or established industry experience
• Hands-on experience with process simulation and optimization tools (commercial or open-source), including steady-state and dynamic modeling.
• Proficiency in Python and scientific/engineering computing ecosystems
• Experience integrating external engineering tools or simulators into automated workflows via APIs, scripting interfaces, or custom wrappers.
• Familiarity with distributed systems, HPC environments, cloud platforms, or scalable compute infrastructure.

Bonus Points For

• Experience developing or integrating agentic frameworks, autonomous planners, or multi-step tool-using AI systems for engineering or scientific domains.
• Experience building computational pipelines, automation systems, or tool-use frameworks for complex engineering or scientific workflows.
• Experience with digital twins, real-time optimization, or model-predictive control frameworks.
• Background in techno-economic analysis (TEA), life-cycle assessment (LCA), or sustainability-driven process design.
• Contributions to open-source engineering software, ML infrastructure, workflow engines, or agent frameworks.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

• For US-based candidates (Cambridge or San Francisco), we expect the base salary for this role to fall between $176,000–$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
• For UK-based candidates, compensation will be determined separately and will be aligned with local market benchmarks and internal leveling.

Your Impact at LILA

Your role in our Physical Sciences division will center on developing the next generation of in silico materials discovery methods, from creating autonomous workflows and data-driven pipelines to building the interface between simulation and AI. You’ll pioneer strategies that enable agents to reason over simulation data, extract latent insights, and guide hypothesis generation and materials design. Your work will expand how we leverage simulation outputs for discovery, accelerating the integration of physics-based modeling and AI reasoning systems. You’ll collaborate with experts in areas spanning simulation, AI agents, and experimental automation to push the boundaries of digital discovery.

What You'll Be Building

• Develop methods and workflows for in silico materials discovery that connect physics-based simulations, generative models, and agentic AI systems.
• Build intelligent pipelines where AI agents can design, launch, interpret, and refine simulations autonomously.
• Design frameworks that utilize simulation data more effectively for prediction, inference, and discovery, including automatic feature extraction, model training, and data-driven exploration.
• Prototype and evaluate new paradigms for simulation-aware agents that can learn from and act on scientific simulations.
• Design data representations, metadata standards, and APIs that enable seamless flow of information between simulations, machine learning models, and experimental databases.
• Create scalable, modular workflows that bridge electronic structure, atomistic, and mesoscale simulations with AI-driven reasoning and hypothesis generation.
• Collaborate with computational scientists, machine learning experts, and platform engineers to integrate in silico discovery pipelines into Lila’s broader scientific superintelligence ecosystem.

What You’ll Need to Succeed

• PhD or equivalent experience in Computer Science, Materials Science, Chemistry, Physics, Applied Mathematics, or related disciplines.
• Strong foundation in in silico materials discovery, computational materials modeling, and/or simulation workflow design.
• Familiarity with large language models and their application in scientific domains, and
• Experience building AI-driven or agentic workflows for scientific automation and discovery.
• Solid programming skills in Python and scientific computing frameworks
• Familiarity with atomistic simulation software and libraries (e.g., VASP, LAMMPS, ASE, Pymatgen, etc.).

Bonus Points For

• Strong publication record in in silico materials discovery, simulation-AI integration, AI-driven inverse design.
• Familiarity with scientific agent architectures, large-scale reasoning systems, or multi-agent frameworks for hypothesis generation and experimental planning.
• Familiarity with ontologies, metadata standards, and data infrastructure for scientific simulations.
• Experience with automated experiment–simulation loops, integrating computational predictions with robotic or cloud-based laboratory platforms.

Your Impact at LILA

As a Scientist on our Physical Sciences team, you will contribute to the development of cutting-edge flow chemistry workflows. You’ll help design, build, and optimize flow chemistry platforms that integrate real-time analytics, advanced control strategies, and AI-driven decision-making. In this role, you’ll work closely with systems engineers and AI scientists to help expand autonomous chemistry capabilities and accelerate discovery at scale. 

What You'll Be Building

• Design & Commission: Architect and develop versatile flow chemistry platforms for autonomous synthesis, ensuring seamless integration with the Lila platform.
• Integrate & Scale: Build, control, and optimize flow reactors and inline analytics. Interface flow chemistry platforms with robotic and sensing systems. 
• Workflow Optimization: Tune flow chemistry platform design and software pipelines for high-throughput closed-loop experimentation with rich metadata capture. 
• Closed-Loop Execution: Collaborate with AI teams to run iterative experiments in real time, enabling fast optimization and discovery cycles.
• Collaboration & Documentation: Work with chemists, material scientists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous flow chemistry.

What You’ll Need to Succeed

• Ph.D. or M.S. in Chemical Engineering, Chemistry, or a related field. 
• ≥ 1 years (for PhD, 4+ years for M.S ) of hands-on experience in flow chemistry, microfluidics, or microreaction engineering. 
• ≥ 1 years of experience with automation, instrumentation, and integrating real-time analytics into experimental workflows. 
• Strong background in homogeneous chemical catalysis and organic synthesis. 
• Proficiency in Python for scripting, data analysis, and instrument control. 
• Excellent problem-solving, communication, and collaboration skills. 

Bonus Points For 

• Prior experience working in an autonomous or self-driving lab chemical lab environment driving organic chemistry transformations. 
• Familiarity with cloud-based instrumentation control and orchestration.
• Hands-on experience with AI-driven experimental design or Bayesian optimization.
• Background in scaling workflows from proof-of-concept to routine, high-throughput operation.
• Contributions to open-source lab automation or scientific software projects.

Your Impact at LILA

Role will lead development and validation of novel mammalian cell based pooled assays. The role will span proof of concept to automated screens to generate highly multiplexed and high dimensional datasets. The role will partner across cell biology, protein design and nucleic acid teams to support biologic development programs with the rapid determination of binding, stability, function, and immunogenicity of a variety of biologics.

What You'll Be Building

• Build next-generation mammalian display based binding, stability, function, and immunogenicity assays.
• Implement state-of-the art multiomic, single cell and in situ sequencing workflows to create novel highly multiplexed assays.
• Partner with protein design, nucleic acid, protein and automation teams to apply these workflows to the development of biologics.
• Closed-Loop Experimentation and Execution: partner closely with engineering and automation to design and exercise platforms for automated, high-throughput experimentation and data-rich workflows. Collaborate with AI team to run iterative experiments in real time, enabling fast optimization and discovery cycles.
• Collaborate, Lead & communicate: Work with cell biologists, synthetic biologists, automation engineers, protein design scientists and data scientists to document systems, share insights, and refine best practices in autonomous science. Mentor junior scientists, align milestones with internal/external collaborators, contribute to IP and publications, and present findings across the org.

What You’ll Need to Succeed

• Ph.D. in Chemical/Biomedical Engineering, Biochemistry, Pharmaceutical Sciences, Immunology, or related field (or M.S./B.S. with 5–8+ years relevant industry experience).
• Expertise with the development and/or application of mammalian display or similar pooled mammalian (perturb-seq, MPRA, etc.) systems
• Expertise with designing, executing and analyzing single cell, in situ or multiomic sequencing based experiments
• Experience designing novel single cell, in situ or multiomic sequencing based techniques
• Experience designing, executing and analyzing flow cytometry and sorting based experiments
• Experience creating highly complex libraries of defined sequences in mammalian cells
• Experience designing, executing and analyzing NGS based experiments

Bonus Points For

• Experience with antibody or cell therapy development
• Imaging experience
• Experience with optical pooled screening or image-based cell sorting
• Experience with encapsulation/droplet/bead/microwell based antibody or cell screening

Your Impact at LILA

We are seeking a Scientist (II) to join our Physical Sciences team. This role will focus on assisting in the design and development of a high throughput chemical synthesis platform, with emphasis on medicinal chemistry and drug delivery applications. The ideal candidate will have experience synthesizing, analyzing, and optimizing novel molecules to build out structure-activity relationships for a library of compounds. This position will work closely with others across the chemistry, formulations, engineering, machine learning, and data science teams to help establish next-generation tools for therapeutic development and drug delivery. Your work will bridge the physical sciences and bioanalytical domains, enabling high-throughput experimentation for closed-loop optimization of organic compounds.

What You'll Be Building

• Design, synthesize, and optimize novel lipids, small molecules, and other combinatorial chemistry compound libraries for drug delivery applications
• Design and deploy high-throughput synthesis strategies, build automated assay platforms, and develop innovative approaches to interrogate large chemical spaces
• Partner closely with chemistry, computational, and automation teams to establish structure-activity relationships for compound libraries to guide iterative design strategies
• Implement data-driven approaches to analyze screening outputs and guide iterative molecule design.
• Work with and manage projects with CDMOs for research-grade synthesis, with considerations towards scale-up of lead compounds
• Establish best practices for screening data quality, reproducibility, and assay robustness.
• Collaborate across disciplines to translate screening hits into validated chemical starting points for therapeutic programs.

What You’ll Need to Succeed

• Ph.D. in Chemistry, Chemical Engineering, or a related field.
• ≥ 1 years of experience with automation, instrumentation, and integrating real-time analytics into experimental workflows.
• Strong background in organic synthesis, with experience designing and synthesizing novel organic compounds.
• Excellent problem-solving, communication, and collaboration skills.

Bonus Points For

• Familiarity with novel lipid design for drug delivery applications
• Prior knowledge and implementation of biodegradability and tolerability design principles, with working knowledge of biological implications of compound moieties
• Prior experience working in an autonomous or self-driving chemical lab environment driving organic chemistry transformations
• Hands-on experience with AI-driven experimental design or Bayesian optimization
• Background in scaling workflows from proof-of-concept to routine, high-throughput operation

Your Impact at LILA

We are seeking a motivated and detail-oriented Senior Research Associate / Associate Scientist to join our high-throughput autonomous chemistry team. This is a hands-on role at the intersection of organic and inorganic synthesis, advanced characterization, and laboratory automation. You will design and execute high-throughput experiments, synthesize small molecules, and perform rigorous downstream analysis while working side-by-side with senior scientists to translate ambitious product goals into scalable experimental workflows that directly drive our company’s growth.

This position offers first-hand exposure to automated chemistry platforms, with real ownership over experiments that inform company strategy and scientific direction. Ideal candidates are execution-driven, thrive in fast-paced laboratory environments, and are eager to build deep technical expertise while contributing meaningfully to next-generation chemical discovery at Lila Sciences.

What You'll Be Building

• Independently execute experiments to synthesize, purify, and characterize organic and inorganic small molecules
• Optimize reactions, perform method development, and interpret analytical data to guide project decisions
• Translate early-stage ideas into reproducible, functional experiments
• Apply retrosynthetic planning to support target molecule synthesis
• Operate Schlenk lines, gloveboxes, and other inert-atmosphere systems for sensitive compounds
• Use PAT tools (UPLC, LCMS, NMR, IR, Fluroescence, DLS) to monitor reactions, ensure quality control, and generate high-quality data for ML workflows
• Leverage automation and AI-driven platforms to accelerate workflows and reduce experimental cycle times
• Collaborate with engineers, ML scientists, and stakeholders to validate model-suggested conditions, analyze trends, troubleshoot issues, and communicate results clearly through reports, discussions, and presentations
• Document results, maintain accurate digital records and adhere to EHS and laboratory best practices

What You’ll Need to Succeed

• M.S. in Chemistry or related discipline (organic, organometallics, catalysis) with 2+ years of hands-on high-fidelity laboratory experience in an academic or industry setting, or B.S. + 5 years
• Hands-on experience in organic/inorganic synthesis, purification, chromatographic techniques, product analysis
• Strong understanding of retrosynthesis, reaction mechanisms, and method optimization workflows
• Proficiency with analytical techniques such as TLC, HPLC, LCMS, NMR, and IR
• Ability to follow SOPs and work safely with diverse chemical reagents and automated platforms
• Ability to thrive in a fast-paced, multidisciplinary research environment
• Required proficiency in using SciFinder, Reaxys, Chemdraw to search public database and literature
• Basic proficiency in Python or other scripting languages for data handling
• Good document practices, strong attention to detail and a proactive, problem-solving mindset
• Effective oral and written communication skills; contributed to internal reports, technical documentation, or peer-reviewed publications

Bonus Points For

• Experience with high-throughput or AI-driven automated platforms
• Authored publications in peer-reviewed journals in chemical catalysis, organic methodology
• Ability to handle air/moisture/light sensitive compounds

Your Impact at LILA

We are seeking a motivated and detail-oriented Associate Engineer to join our high-throughput Research Operations team. In this role, you will focus on materials characterization of materials using spectroscopy and microscopy techniques

You will gain hands-on experience with state-of-the-art automation technologies while contributing directly to projects that drive our company’s growth.

This is an excellent opportunity for candidates excited to learn engineering principles, work with advanced laboratory automation, and develop a strong foundation in scientific operations in a dynamic environment.

What You'll Be Building

• Perform materials characterization techniques including SEMXRF, XRD, Optical Microscopy, Nanoindentation, and Profilometer
• Prepare reagents, solutions/electrolytes , samples, and consumables to ensure seamless continuation of experiments across shifts
• Follow detailed standard operating procedures (SOPs) to ensure accuracy, reproducibility, and throughput
• Monitor workflow performance, troubleshoot common issues, and escalate when necessary to ensure continuity between shifts
• Record, organize, and maintain experimental data with high attention to detail
• Identify opportunities to improve efficiency and streamline processes across shift operations
• Flag unusual features or results for scientist review
• Collaborate with scientists and engineers to support diverse projects across life sciences and physical sciences

What You’ll Need to Succeed

• Bachelor’s degree in Chemistry, Physics, Chemical/Materials Engineering, or a related field (or equivalent laboratory experience)
• Attention to detail and strong organizational skills
• Basic understanding of electron microscopy principles
• Hands-on SEM experience (academic or industry). EDS experience is nice to have.
• Experience with sample preparation techniques: sputter coating

Bonus Points For

• Familiarity with surface characterization techniques methods: XRF, optical microscope, XRF, XRD, nanoindentor, profilometer.
• Experience working in high-throughput production environments with a focus on scalability, efficiency, and accuracy
• Basic engineering skills for troubleshooting characterization tools for microscopes, x rays, and lasers
• Familiarity with automated workflows and techniques to operate and generate custom scripts

Your Impact at LILA

As a ML Research Scientist - Multimodal Data Extraction, you will advance Lila’s vision of scientific superintelligence by developing foundation models that autonomously read, interpret, and structure scientific knowledge across text, images, and experimental data in the physical sciences. Your research will help unify the world’s scientific information into machine-understandable form, powering reasoning, prediction, and autonomous discovery across materials science and chemistry.

What You'll Be Building

• Research and develop AI systems that extract and structure knowledge from diverse scientific sources.
• Design and fine-tune large language, multi-modal and specialized models for factual, interpretable data extraction.
• Build scalable pipelines for unstructured and heterogeneous scientific data, integrating text, tables, and visuals.
• Collaborate with domain experts to align extracted data with real-world discovery workflows.
• Publish research that advances the state of the art in multimodal understanding and AI-driven knowledge extraction.

What You’ll Need to Succeed

• PhD (or equivalent research experience) in Computer Science, Chemistry, Materials Science, or related field.
• Expertise in machine learning, NLP, and vision–language modeling using PyTorch and Hugging Face Transformers.
• Proven ability to train, fine-tune, and evaluate LLMs and multimodal models for scientific data extraction.
• Strong understanding of data structures and representations used in the physical sciences.
• Demonstrated research impact through publications, preprints, or open-source work (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, Scientific Journals).

Bonus Points For

• Experience with multimodal fusion architectures and document-level understanding.
• Knowledge of scientific document parsing (OCR, table extraction, figure-caption linking).
• Familiarity with knowledge graph construction or reasoning systems for science.
• Experience with noisy or heterogeneous real-world scientific data.
• Collaborative mindset and passion for advancing AI in the physical sciences.

Your Impact at LILA

Your role in our Physical Sciences division will focus on designing and implementing state-of-the-art simulation approaches to model transport, kinetics, rare events, and reaction networks, and integrating them with AI-driven platforms for materials discovery. Your work will be integral to our efforts in predicting, designing, and controlling the behavior of complex materials and molecular systems, and their acceleration via agentic AI. You will partner with diverse teams at Lila, including machine learning experts working on scientific superintelligence and materials science experts performing real-world experiments.

What You'll Be Building

• Develop and extend molecular dynamics and Monte Carlo algorithms to capture rare events, non-equilibrium processes, transport phenomena, and mapping complex reaction networks.
• Build scalable simulation workflows that integrate statistical mechanics methods with machine learned interatomic potentials and agentic AI frameworks.
• Design methods for coupling dynamics simulations with experimental observables to enable closed-loop verification and discovery with automated labs.
• Collaborate with computational scientists, machine learning experts, and platform engineers to advance the fidelity and scalability of simulation-driven materials discovery.
• Establish reproducible, modular software pipelines for statistical mechanics and dynamics simulations that can be deployed on HPC and cloud-based infrastructure.

What You’ll Need to Succeed

• PhD or equivalent research/industry experience in Physics, Chemistry, Chemical Engineering, Mechanical Engineering, Applied Mathematics, or related fields.
• Strong background in statistical mechanics, free energy calculations, reaction mapping, non-equilibrium dynamics, and rare-event sampling.
• Demonstrated expertise with molecular dynamics, Monte Carlo, and/or kinetic simulation software and frameworks (LAMMPS, GROMACS, OpenMM, HOOMD, etc.).
• Solid programming skills and experience with scientific computing (Python, C/C++, MPI, CUDA, etc.).
• Experience running and automating simulations on HPC and/or cloud environments at scale.

Bonus Points For

• Strong publication record applying advanced statistical mechanics or dynamics simulations to molecular and materials systems, including but not limited to molecular/biomolecular systems and solid-state materials and interfaces.
• Prior work in coupling dynamics simulations with data-driven, AI-based, and/or agentic frameworks.
• Good familiarity with machine learning frameworks (PyTorch, JAX, TensorFlow, etc.)
• Prior experience working with machine learned interatomic potentials, including model training, fine-tuning, and data generation
• Worked closely with experimental teams to extract and corroborate experimental observables from dynamics simulations

Your Impact at LILA

We are seeking a (Senior) Research Associate to join our Life Sciences team. This role will focus on formulating lipid nanoparticles (LNPs), functionalizing them with targeting ligands, and characterizing the resulting targeted LNPs (tLNPs). The ideal candidate will have hands-on expertise in LNP formulation and characterization, bioconjugation, protein characterization, and automation technologies. Your work will unlock new understandings in the delivery space by enabling a high-throughput closed-loop screening cascade for tLNPs. This position will work closely with others across the protein, cell biology, automation, chemistry machine learning, and data science teams to help establish high-throughput next-generation tools for targeted nucleic acid delivery.

What You'll Be Building

• Design, execute, and characterize (DLS, ribogreen, TNS, etc.) LNP formulations across multiple scales and mixing modalities
• Develop and refine high-throughput ligand conjugation and purification methods, employing automation and robotics to increase throughput
• Collaborate with cell assay and antibody specialists to screen hits across a variety of tissue targets in in vivo models
• Collaborate with chemists, biologists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous flow chemistry
• Write, implement, and maintain Standard Operating Procedures (SOPs) for both existing and new lab processes

What You’ll Need to Succeed

• MSc in Chemical Engineering, Biomedical Engineering, Pharmaceutical Sciences, or a related field with 3+ years, or BSc with 5+ years, of hands-on experience in targeted LNP production, or related experience. Industry experience strongly preferred
• Strong working knowledge of bioanalytical techniques (e.g., DLS, fluorescence spectroscopy, electrophoresis, in vitro assays)
• Experience with protein and antibody design and characterization
• Familiarity with automation and high-throughput workflows
• Excellent troubleshooting, communication and collaboration skills, with a proven ability to work effectively across interdisciplinary teams

Why Join Us?

Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR^ON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

The Senior Associate Scientist will play a hands-on role in discovery and translational biology, leading assay development and generating mechanistic insights to support oncology programs from lead optimization through biomarker development. This individual will partner cross-functionally to deliver high-quality, decision-driving data and contribute to advancing novel targets.

• Design, develop, and optimize multiplexed cell-based and high-throughput assays to ensure robust, reproducible, and scalable data generation
• Improve assay throughput and efficiency through automation or semi-automation, proactively identifying risks and refining experimental strategies
• Drive mechanistic understanding of novel oncology targets through hypothesis-driven experimentation (e.g., CRISPR, knockdown, tool compounds, rescue strategies)
• Integrate internal data, literature, and public datasets to inform experimental design, interpret results, and refine scientific hypotheses
• Contribute to biomarker discovery efforts and support translational strategy development
• Collaborate cross-functionally with chemistry, DMPK, in vivo pharmacology, and data science teams to advance programs from hit-to-lead through IND-enabling studies
• Support assay transfer to CROs, including data review, troubleshooting, and performance tracking
• Present findings clearly to project teams and maintain rigorous documentation, including ELN entries and SOP development

What you’ll need to be successful:

• Education & Experience:
  • Bachelor’s degree with 5+ years or Master’s degree with 4+ years of industry experience in a relevant field
  • Experience in discovery biology, with exposure to oncology or related therapeutic areas preferred
• Technical Expertise:
  • Strong hands-on experience developing and executing cell-based and high-throughput assays, including automation
  • Quantitative approach to assay design and data quality (controls, reproducibility, robustness metrics)
  • Experience designing and executing experiments independently and generating actionable insights from complex datasets
  • Familiarity with a subset of the following:
    • CRISPR/Cas9, gene editing/knockdown, overexpression systems
    • qPCR/RT-qPCR, Western blotting, flow cytometry
    • Reporter assays (e.g., luciferase, NanoBRET), protein–protein interaction assays
    • Mammalian cell culture and functional assays (e.g., proliferation, apoptosis)
    • High-throughput screening formats (e.g., 384-well)
    • Omics approaches (e.g., RNA-seq, proteomics) preferred
    • Automation platforms, ELN systems (e.g., Dotmatics), and SOP authorship
  • Core Capabilities:
    • Strong experimental rigor and data-driven decision-making
    • Ability to manage multiple projects and priorities in a fast-paced environment
    • Effective cross-functional collaboration and clear scientific communication
    • Ownership mindset with ability to independently drive workstreams
  • Demonstrated ability to utilize AI tools for day-to-day work; baseline proficiency is expected, and advanced or innovative use of AI is a strong plus
  • Able to work on-site and attend in-person meetings

Core Values

Parabilis Medicines is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent. We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused. We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In. We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary range for this position is $88,000–$108,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis Medicines values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

30 Acorn Park Drive    |     Cambridge, MA 02140    |    www.parabilismed.com

Why Join Us?

As a member of the Parabilis Medicines team, you will be a part of an organization dedicated to creating extraordinary medicines for diseases with urgent unmet needs, harnessing our proprietary peptide platform to transform treatment possibilities for patients. Parabilis is a clinical-stage biopharmaceutical company dedicated to unlocking high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities.

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and ARON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

We are seeking a Scientist with a chemical biology mindset and strong experimental skills to help advance and scale our AI-driven peptide discovery programs. Parabilis has built a powerful high-throughput mass-spec driven multiplexed screening platform that enables us to navigate chemical space and optimize our Helicons to target undruggable proteins. In this role, you will develop and improve experimental methods for understanding Helicon activity and properties, leveraging a range of laboratory and computational tools, and collaborating as part of a cross-functional team. Over time, you will develop an understanding of Helicon design and leverage high-quality assay data to advance drug discovery programs.

Specific responsibilities include:

• Develop and improve experimental screening assays: design, optimize, and productionize biochemical and cell-based assays that allow us to measure drug-like properties at scale across multiple programs.
• Advance automation in practice: implement automation for existing assays, and construct new assays with laboratory robotics in mind, troubleshooting and iterating workflows to achieve consistent performance and to facilitate integration with digital and AI/agent-driven automation.
• Build script-based tools to scale execution: develop reusable scripts and lightweight tools that reduce manual steps and improve experiment setup, tracking, QC, and reporting for broad team use.
• Drive decision-quality data and learning: apply quantitative rigor to assay performance and data QC and translate outputs into insights that inform next experiments and, over time, Helicon optimization.  
  

What you’ll need to be successful:

Required qualifications

• PhD in Chemical Biology, Biochemistry, Cell Biology, or a related discipline, with 2-4 years of postdoctoral and/or industry experience.
• Strong hands-on experience developing, optimizing, and executing experimental assays (biochemical, biophysical, and/or cell-based), with demonstrated ability to translate complex biological questions into robust, scalable assay formats.
• Quantitative approach to assay quality and performance, including comfort with controls, variability, robustness, and data QC to produce decision-quality readouts.
• Demonstrated scripting and tool-building experience beyond ad hoc “vibe coding,” with examples of using code to automate analyses, streamline workflows, or solve recurring operational problems.
• Ability to work cross-functionally and communicate clearly with chemistry, biology, and data-focused colleagues.
• Demonstrated use of AI tools in your current role and responsibilities is required; advanced or innovative use is a plus.

Preferred qualifications

• Experience improving lab throughput through automation or semi-automation, or strong aptitude and interest in learning and applying automation technologies in a screening environment.
• Familiarity with high-throughput screening concepts and scaling assay workflows to support large sample numbers.
• Working knowledge of peptide chemistry and/or peptide discovery concepts is a plus but not required.

Ways of working that matter here

• A builder mindset with strong scientific judgment: you identify bottlenecks, choose the least-resistant path to improvement, and execute with urgency.
• Curiosity for emerging technologies and a practical approach to evaluating what could improve workflow robustness, automation, or assay quality.
• Highly collaborative, low-ego, can-do attitude with consistent follow-through and strong ownership of results.

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent. We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused. We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In. We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary range for this position is [$120,000–$145,000] per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

About the Role

Accelerating clinical research is one of the defining challenges in healthcare. Promising therapies exist that patients can't access because the operational infrastructure to run clinical trials efficiently doesn't exist yet. We're building it. That means designing technology systems that bring order to a fragmented landscape of clinical data sources, automating the operational work that slows trials down, and turning real-world clinical data into a foundation for predictive intelligence.

We're looking for a Staff Data Scientist to be the person who understands our data deeply enough to know what's possible and curious enough to prove it. We have a truly unique data set within the industry, connecting clinical data (emr, endoscopic video, etc…) to trial data across 80+ trial sites. We're looking for someone who wants to dig deeply into this data - to understand its structure, its gaps, what it can tell us - and connect that understanding to real outcomes for sites and patients. The landscape is evolving rapidly, and the right person will have a point of view on how to apply new capabilities to our specific data and problems as they emerge.You'll work hands-on with the data, structure experiments, evaluate what's modelable, and directly influence what we build and how. This role sits at the intersection of data science, product strategy, and ML: you'll lay the foundation for our predictive capabilities and shape what that function becomes.

This is an opportunity for someone who wants to be part of a small, fast-moving engineering team at a formative stage. You'll shape what gets built, how decisions get made, and what the team becomes.

Responsibilities

• Work with clinical, video, and clinical trial operational data to understand what's there, what's meaningful, and how we can use it to drive a more efficient clinical trial system
• Design and run experiments that determine what's worth building
• Stay close to the evolving ML and model landscape and bring a point of view on how new capabilities apply to our data and problems
• Define the path from raw data to product and operationalization: what to model, how to evaluate it, and when it's ready to ship
• Partner with product and engineering to translate findings into concrete product decisions
• Identify opportunities where our data creates unique predictive advantages
• Evaluate where we should build, where we should partner, and where existing approaches fall short
• Help shape the engineering culture of a small, growing team: how technical decisions get made, how problems get debated, what rigor looks like in practice

What We’re Looking For

Required Qualifications

• 5+ years of experience in data science, applied ML, or quantitative research, with significant time spent hands-on with data
• Experience with healthcare data, clinical research, or life sciences
• A deep curiosity to understand data and connect it to the real world
• Deep experience designing and running experiments: you know how to structure a question, test it honestly, and draw conclusions that hold up
• Strong statistical foundations and the judgment to know when a result is meaningful versus interesting
• Fluent in Python and SQL, comfortable working across the data stack from exploratory analysis through to production-ready pipelines
• Experience working across data science, product, and engineering: you can influence what gets built, not just analyze what exists
• Have worked with complex, messy, real-world data and know how to make it useful without pretending it's clean
• Knowledgeable about ML capabilities and frameworks, with the judgment to know when something is genuinely applicable versus hype
• Can communicate findings clearly to technical and non-technical audiences, and make a persuasive case for what to build next

Preferred Qualifications

• Experience working at growth stage startups (strongly preferred)
• Experience with medical imaging or video data
• Familiarity with clinical trial operations, disease classification, or patient identification problems
• Experience building or defining the roadmap for an ML function from early stages
  • A track record of data science work that directly changed product direction

About the Translational Sciences Team

We are building a dynamic drug discovery team in Boston, as part of Isomorphic Labs’ approach to transform how drugs are designed. Translational Sciences is an essential component of this effort, establishing and evolving our biological understanding of how to correct dysregulated systems in disease. This team will have impact across the full breadth of our portfolio, from critical input on target selection to essential partnership on biomarker development, to enable pharmacodynamic modulation and target engagement in the clinic.  Domain expertise will be critical to design translational strategies for programs, evolving our understanding of mechanisms and modes of action as programs progress.  This team will be highly collaborative and need to establish strong scientific relationships with multiple groups in the company, from Medicinal Chemists to Applied Machine Learning Scientists, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios.

What you will do 

• Lead the preclinical Translational Science strategy in close collaboration with the Computational Biology, Preclinical Development and Translational Medicine teams, ensuring lifecycle-spanning screening cascades and biomarker assays are in place to guide programs toward clinical success.
• Ensure scientific rigor and "decision-quality" data across all local programs.
• Partner with the VP, Head of Drug Discovery, Cambridge, MA to recruit and retain a world-class team of scientists.
• Maintain a seamless collaborative loop with the Head of Translational Sciences, London to ensure resource sharing, protocol alignment, and unified scientific standards.
• Direct all in vitro and in vivo biology operations in Cambridge, MA through a network of CROs to generate, ingest and interpret high quality experimental data efficiently to support all aspects of our drug design programs from HitID through to IND.
• Foster a site culture of high accountability, rapid iteration, and scientific curiosity.
• Serve as a key internal consultant and advisor for global target discovery, providing critical technical assessment, feasibility analysis, and translational "stress testing" for new targets under consideration.
• Collaboratively execute program progression and determine resource allocation.
• Facilitate the transfer best practices and know-how between the UK and US sites to maximize R&D efficiency.
• Manage relationships with CROs and academic collaborators to extend the site’s internal capabilities.

Skills and qualifications 

Essential:

• PhD in relevant Biological Sciences.
• Solid foundation in Translational Sciences with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting, with a clear trajectory of increasing responsibility. 
• Proven track record of successfully navigating the discovery to IND transition, demonstrating mastery of molecular mechanisms.
• Track record of delivering multiple programs by formulating and implementing fit for purpose biological strategies to progress from hit ID through to IND as a program biology lead.
• Demonstrated experience in line management, mentorship, and developing scientific talent.
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Ability to work with computational biologists to define and implement patient and biomarker selection strategies
• Experience of working with and closely managing CRO resource. 
• Strong track record of scientific achievement, evidenced by publications, patents, and presentations.
• Genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.

Nice to have:

• Experience working in an AI/ML led drug discovery environment.
• Experience of  working with product /data scientist to build or configure data analysis systems for diverse  program datasets but specifically for pharmacological data.
• Experience of diverse chemical modalities e.g. molecular glues.

Company description

Serif Biomedicine is a privately held, early-stage biotechnology company developing a novel approach to gene therapy that can address currently untreatable diseases. It was founded by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and grows first-in-category life sciences companies.

Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Syros Pharmaceuticals (SYRS), Seres Therapeutics (NASDAQ:MCRB), Generate Biomedicines, Tessera Tx, Evelo Biosciences (EVLO), and Indigo Agriculture.

The role

We are seeking a highly experienced Lipid Nanoparticle (LNP) Formulation Senior Scientist to lead the design, execution, and interpretation of advanced Design of Experiments (DOE) strategies to drive innovation in next-generation LNP formulations. This role will play a central role in shaping formulation and delivery strategies for nucleic acid therapeutics within a dynamic and collaborative research environment.

The successful candidate will not only develop, optimize, and characterize LNP systems, but also lead the design and establishment of a high-throughput LNP screening platform spanning in vitro systems and small and large animal models. This includes defining experimental frameworks, selecting and implementing appropriate assays, and building scalable workflows to accelerate candidate evaluation and selection.

As a senior scientific contributor, this individual will be expected to operate with a high degree of independence, influence cross-functional program direction, and identify innovative solutions to advance platform capabilities. The role also includes mentoring junior scientists and contributing to the broader scientific strategy through internal leadership and external scientific engagement.

Key responsibilities

• Drive the development, optimization, and implementation of a high-throughput LNP screening platform across small and large animal models, including experimental design, assay selection, and data analysis pipelines.
• Independently define scientific strategies and experimental roadmaps aligned with program goals.
• Serve as a scientific lead for one or more programs, influencing cross-functional decisions across biology, formulation, and translational teams.
• Identify technical gaps and proactively propose innovative solutions to improve platform capabilities and throughput.
• Mentor junior scientists and contribute to building a strong, collaborative scientific culture.
• Communicate findings clearly to internal stakeholders and external partners; contribute to publications, patents, and regulatory documentation.
• Stay at the forefront of LNP delivery technologies and emerging screening methodologies, integrating new approaches where appropriate.

Professional experience and qualifications

• PhD or MS in Chemistry, Pharmaceutical Sciences, Chemical Engineering, Materials Science, or a related field and 5+ years of industry experience 
• Proven track record of independently leading research projects and delivering impactful results.
• Demonstrated experience in nanoparticle/LNP design, screening, and in vivo evaluation, preferably including large animal models.
• Experience in developing or scaling high-throughput screening platforms is strongly preferred.
• Strong understanding of experimental design, statistics, and data interpretation.
• Evidence of scientific leadership (e.g., mentoring, leading collaborations, publications, patents).
• Excellent communication and cross-functional collaboration skills.
• Strong hands-on experience with LNP formulations, including formulation development and optimization

What We Offer

• Opportunity to work at the forefront of LNP formulation innovation
• Collaborative, science-driven culture with high impact research
• Competitive compensation and benefits package

ABOUT FLAGSHIP PIONEERING

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.

Flagship has been recognized twice on FORTUNE Change the World list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company annual list of the World Most Innovative Companies. Learn more about Flagship https://url.us.m.mimecastprotect.com/s/xLXBCqxk3LTk9pwcZf3CEkjif?domain=flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $126,000 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL87 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL87's good faith estimate as of the date of publication and may be modified in the future.

Company Summary 

We are building a new venture, FL122, pioneering genomic technologies at the intersection of human health and assisted reproduction. The company was founded by Flagship Pioneering, an innovative enterprise that conceives, creates, resources, and grows first-in-category life sciences companies. Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Generate Biomedicines, Tessera Therapeutics, and Quotient Therapeutics. We are an equal opportunity employer. 

Position Summary 

We are seeking a Scientist with experience at the intersection of reproductive biology and molecular biology to help build the experimental foundation of the company’s scientific platform. As an early scientific team member, you will contribute to the development of core laboratory workflows spanning human gamete handling and molecular characterization, support the establishment of technical standards, and help execute the experimental strategy in close collaboration with senior scientists and leadership. 
 
We are looking for someone who is highly hands-on, adaptable, and excited to operate across disciplines. The ideal candidate brings a strong foundation from IVF or embryology laboratory environments, combined with experience in molecular biology techniques and a willingness to learn and implement new methods. This role requires attention to detail, comfort working with sensitive human samples, and a collaborative mindset suited for a fast-paced startup environment. 

Key Responsibilities 

• Perform and support IVF laboratory procedures, including preparation and handling of human gametes in a BSL2 environment with strict adherence to quality and reproducibility standards 

• Execute workflows related to ART techniques such as intra-cytoplasmic sperm injection (ICSI) and related embryology methods, contributing to protocol optimization and standardization 

• Conduct molecular biology experiments, including nucleic acid extraction, amplification, and QC from low-input or sensitive samples 

• Contribute to the development and optimization of workflows for integrating embryology procedures with downstream molecular analyses 

• Support implementation of instrumentation, reagents, and workflows to enable robust and scalable experimental operations 

• Assist in transcriptomic workflows (e.g., RNA-seq), including sample preparation, library preparation, and coordination with sequencing efforts 

• Analyze and communicate experimental results clearly, troubleshoot challenges, and iterate on protocols 

• Collaborate across internal teams and incorporate feedback from external advisors into experimental plans 

Requirements 

• Prior hands-on experience in IVF or embryology laboratory settings, including handling human gametes and performing procedures such as ICSI or related workflows  

• Ph.D. in biology, molecular biology, genetics, reproductive biology, or a related discipline strongly preferred; exceptional candidates with a Master’s degree/ relevant hands-on experience will also be considered  

• Strong foundation in molecular biology techniques, with demonstrated ability to learn and adapt to new experimental methods  

• Experience with RNA sequencing workflows; exposure to single-cell RNA sequencing is a plus but not required  

• Demonstrated ability to execute and troubleshoot experiments independently, particularly in low-input or sensitive sample contexts  

• High attention to detail and commitment to quality, especially when working with human-derived samples  

• Comfort working in a fast-moving, early-stage startup environment with a collaborative and proactive mindset 

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $100,000 - $143,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL122 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL122's good faith estimate as of the date of publication and may be modified in the future.

ABOUT PIONEERING INTELLIGENCE 

Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship’s integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.

THE ROLE

We are seeking a Principal Scientist (Embedded ML/Computational) to lead multiple AI/ML or computational projects across early stage ventures, as a part of Flagship’s company origination process. You will define and deliver pragmatic AI strategies, oversee method and platform development (e.g., systems design, drug design, molecular modeling, systems biology, protein design, LLM/agentic workflows), and ensure rigor in model development, benchmarking, scaling, and reporting. You will manage cross functional contributors as applicable, influence company direction, and represent PI to venture teams and external partners. The ideal candidate is a self-directed serial deep diver - someone who can move from protein design one week to mass spec or docking pipelines the next and then spin up LLM based agents that automate scientific workflows. 

KEY RESPONSIBILITIES

• Program Leadership: Lead development, implementation, control, and reporting of several AI/ML or computational projects within assigned ventures in line with broader strategic plans of PI and Flagship, budgets, and timelines. 
• Technical Ownership: Take a specialized technical role on project teams to oversee method development, pipeline development, and LLM based agent/workflow design; drive benchmarking, scaling, and implementation into production grade systems. 
• Best Practices: promote operational excellence in AI projects by educating cross-functional collaborators. 
• Team Leadership: Manage and/or coordinate internal and external scientists/engineers and crossfunctional project teams as applicable; mentor early hires; support recruiting and interview. 
• Planning & Resourcing: Contribute to project planning, including budgets, resources, and timelines; surface risks and tradeoffs early with clear options. 
• Landscape & Strategy: Independently scout emerging literature and the AI/ML landscape; synthesize concepts to propose new development strategies and identify opportunities for PI and venture portfolios. 
• Representation & Community: Represent PI to portfolio companies and external partners; act as a recognized subject matter expert; actively participate in scientific conferences and meetings. 
• Communication & Influence: Influence the course of projects and technical approaches; adapt and present complex findings to diverse audiences to support meaningful interpretation and action. 

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• Master’s, or PhD in a relevant field (e.g., machine learning, mathematics, statistics, computational sciences) with 5+ years' experience scientific/engineering/computational in academic, pharmaceutical, or biotechnology settings; industry AI/ML experience preferred. 
• Experience driving results directly or indirectly through teams of engineers/scientists in dynamic, fastpaced, entrepreneurial, and technical environments. 
• Clear evidence of sustained independent thought and creativity driving high impact, cross disciplinary AI/ML projects. 
• Successful track record of leadership and contribution to decision making on progression of AI/ML models within projects or programs. 
• Depth across multiple core tools and concepts, including Python; modern ML frameworks (PyTorch or JAX/TensorFlow); version control; databases; deep learning architectures; and relevant informatics software. 
• Consistent record of outstanding performance reflected in publications, patents, or high impact internal reports where applicable 

Preferred Qualifications 

• Breadth across domains such as protein modeling/design, proteomics/mass spec, cheminformatics/docking/ADMET, biophysics/MD, and LLM/agentic automation. 
• MLOps expertise: data contracts and lineage (e.g., DVC/LakeFS), experiment tracking (MLflow/W&B), secure AWS infrastructure (S3, Batch/ECS/EKS, SageMaker), Docker, IaC (Terraform/CDK), and CI/CD (GitHub Actions). 
• Generative modeling (diffusion/flow/VAEs) for sequences, graphs, or 3D structures; docking rescoring (e.g., gnina, DiffDock) and pose quality metrics. 
• Workflow orchestration (Airflow/Prefect/Argo), data warehouses (Redshift/Snowflake), vector search (FAISS/pgvector), and lightweight internal tools (FastAPI, Streamlit/Gradio). 
• Experience mentoring early hires, acting as interim Head of ML, and contributing to hiring plans and interview processes at startups. 

WHY PIONEERING INTELLIGENCE

• Operate at the frontier: Build and deploy AI/ML that directly powers discovery and decision making across multiple new ventures. 
• Own the full stack: From scoping and data contracts to models, MLOps, and internal UIs—ship endtoend systems that scientists rely on daily. 
• Compound impact: Convert one off wins into shared libraries and templates adopted across the PI portfolio. 
• Work with founders: Partner closely with venture leadership and PI platform engineers; influence strategy through hands on delivery. 
• Grow fast: Stretch across domains, take on situational leadership, present at conferences, and help shape first ML teams. 

ABOUT FLAGSHIP PIONEERING:

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

#LI-MB1

The salary range for this role is $208,000 - $286,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence’s good faith estimate as of the date of publication and may be modified in the future.

The Company

Flagship Labs 110 Inc. (FL110) is a privately held, early-stage technology company developing a fully integrated, end-to-end platform to enable next generation proteomics. Our platform integrates groundbreaking innovations in bioengineering, machine learning, and custom microelectronics to offer a level of precision and insight never before achieved.

FL110 is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. We are uniquely cross-functional and collaborative. Our teams thrive in unstructured and creative environments. Therefore, we seek individuals with an inclusive mindset and a diversity of thought.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

The Role:

FL110 is seeking a creative and talented (Senior) Scientist, Nanopore to join our team. Leveling is flexible based on experience. This role will focus on developing nanopore sensing technologies and will join a team creating a nanopore based protein reading system.

You will be part of a dynamic, cross-functional team, working closely with chemists, bioinformaticians, software developers, and hardware engineers. The ideal candidate has a strong background in nanopore technology, specifically with protein translocation, as well as either experience in biotech industry or a record of scientific achievement.

Key Responsibilities

• Conduct advanced research in nanopore technology to drive technological advancements and deliver impactful results
• Develop and implement innovative research strategies and methodologies
• Collaborate with cross-functional teams to align research activities with company objectives
• Manage resources and timelines effectively
• Foster a culture of innovation and scientific excellence within the team
• Collaborate with internal and external stakeholders, including academic institutions, industry partners, and regulatory bodies
• Present research findings at scientific conferences and contribute to patent applications
• Communicate complex scientific concepts and project updates to diverse audiences, including non-scientific stakeholders

Basic Qualifications

• Ph.D. in Physics, Molecular Biology, or related field
• Demonstrated experience in nanopore experimentation and protein translocation
• Experience with python-based data analysis and R
• Proven track record of scientific achievements demonstrated through publications, patents, and successful project completions
• Strong leadership and project management skills
• Excellent problem-solving abilities, analytical skills, and attention to detail
• Strong communication skills, both written and verbal, with the ability to convey complex scientific information to diverse audiences
• Ability to work independently and collaboratively in a fast-paced, dynamic environment

Nice-to-Haves

• Demonstrated expertise in protein biochemistry including protein expression and purification

Who Will Love This Job

• A rigorous individual with a curious mind and a love of learning who enjoys working in a fast-paced environment with a driven and collaborative team

About Flagship Pioneering

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $100,000 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL110 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL110's good faith estimate as of the date of publication and may be modified in the future.

COMPANY DESCRIPTION

Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health, sustainability and beyond exponentially accelerate scientific progress in areas ranging from disease detection and treatment and nature-positive agriculture to novel applications of AI that are driving the creation of new technologies.   

What sets Flagship apart is our ability to advance science and technology by uniting innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet.   

Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. 

THE ROLE

We are seeking a Senior Scientist to lead the design, characterization, and performance optimization of aerosolizable particle systems. This role will be responsible for developing a foundational understanding of how engineered particles behave during generation, dispersion, and transport in air, and translating that understanding into robust, scalable material and system designs.

The Senior Scientist will operate at the interface of materials science, aerosol physics, and experimental engineering — owning the development of aerosol testing capabilities, guiding experimental strategy, and linking particle design to airborne performance. This individual will play a critical role in shaping early technical direction, establishing core methodologies, and driving progress from concept through validation.

This is a highly cross-functional role, working closely with formulation, process development, and hardware teams to ensure tight integration between particle design, production methods, and real-world deployment constraints.

KEY RESPONSIBILITIES

• Lead the design and optimization of particle systems for aerosolization, with ownership over key parameters including size distribution, morphology, density, and dispersibility;
• Develop and scale experimental capabilities for aerosol generation and testing, including selection, design, and validation of dispersal systems and measurement tools;
• Define and execute experimental strategies to understand relationships between particle properties, environmental conditions, and airborne behavior;
• Characterize aerosol performance using appropriate instrumentation (e.g., particle sizers, optical counters, flow diagnostics), and translate findings into design rules and system improvements;
• Develop and apply computational approaches to model aerosol physics and particle dispersal, integrating atmospheric transport and dispersion models or Lagrangian particle simulations with experimental data to inform particle and system design;
• Collaborate cross-functionally with formulation and process development teams to align particle production methods with aerosol performance requirements;
• Establish best practices, workflows, and technical standards for aerosol experimentation, including calibration, reproducibility, and data quality;
• Interpret complex datasets and communicate insights clearly to guide technical and strategic decision-making;
• Contribute to system-level thinking around particle generation, dispersion, and scale-up, incorporating constraints from real-world operating environments;
• Mentor junior scientists and contribute to building a strong experimental and technical culture within the team.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• PhD in aerosol science, chemical engineering, mechanical engineering, physics, materials science, or a related discipline, with 5+ years of relevant industry or applied research experience (or Master’s/Bachelor’s with significant additional experience);
• Deep expertise in aerosol science, including particle generation, transport, and measurement, with a strong understanding of how particle properties influence airborne behavior;
• Hands-on experience with aerosol instrumentation (e.g., SMPS, APS, optical particle counters) and the ability to design and interpret complex experiments;
• Strong foundation in transport phenomena, fluid dynamics, and particle physics as applied to airborne systems;
• Experience working with particulate materials, including connecting physical properties (size, shape, density, surface characteristics) to performance outcomes;
• Experience with modeling aerosol transport and dispersion using Lagrangian particle dispersion models, computational fluid dynamics (CFD) simulations, or related numerical approaches is a strong plus;
• Demonstrated ability to design experimental systems and build or adapt setups for aerosol generation and testing;
• Proven ability to lead technical projects in fast-paced, early-stage environments, balancing hands-on work with strategic thinking;
• Strong communication and documentation skills, with the ability to synthesize complex technical findings into clear, decision-relevant insights;
• Demonstrated curiosity, adaptability, and comfort working across disciplines to translate early-stage scientific ideas into functional systems.

LOCATION:  Cambridge, MA

ABOUT FLAGSHIP PIONEERING:

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

#LI-TL1

The salary range for this role is $126,000 - $159,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Protocos currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Protocos's good faith estimate as of the date of publication and may be modified in the future.

Company Description: 

In today’s healthcare system, disease diagnosis often relies on invasive procedures, such as biopsies, which enable direct interrogation of cellular and tissue health at the suspected source of disease. Due to their invasiveness, cost, and general inconvenience to the patient, biopsies are often conducted after onset of symptomatic disease presenting one of the largest barriers to delivering interventions early in disease progression when they are likely to be most impactful. Flagship Labs 103, Inc. is a privately held early-stage company that is building advanced technological and computational platforms to pioneer the detection of cellular dynamics from minimally invasive biospecimens that can be leveraged to connect individuals to the most effective interventions to prevent onset and progression of disease

Job Description:

We are seeking an experienced and motivated Senior Scientist to join and lead our conjugation efforts to drive FL103’s programs forward. Ideal candidates will be self-motivated, independent, and committed to the generation of high-quality data within a fast-paced and innovative research team. The Conjugation Biochemist will support ongoing bioconjugation projects in several research and development areas.

Essential Responsibilities:

• Design, synthesis, purification and analysis of oligonucleotide-conjugates on antibodies and other modalities. Develop and optimize conjugation protocols using established and novel chemistries and technologies as part of an assay development platform.
• Collaborate closely with the assay development team to guide and optimize conjugates to support FL103’s programs.
• Work as part of a cross-functional team to manage and maintain progress against multiple project timelines, deliver routine updates, and communicate progress to the team.
• Establish and maintain excellent working relationships with critical collaborative partners throughout the company to advance discovery research activities to pre-clinical development.
• Contribute to the preparation of research reports and presentations for internal project teams, leadership team, and external audiences.
• Maintain updated and well-organized lab notebooks and batch records.

Required Qualifications:

• Ph.D. in Biochemistry, Chemistry, or related scientific discipline
• 5+ years of bioconjugation-related industrial experience, preferably in designing, preparing, and validating oligonucleotide conjugates.
• Understanding project timelines and deliverables and plans/coordinate project work accordingly with departmental, functional, and external stakeholders.
• Strong problem-solving skills and a proactive attitude towards exploring new approaches.
• Demonstrates strong written and verbal communication skills, with the ability to clearly present complex scientific data to cross‑functional and senior leadership teams.
• Hands-on expertise with current and cutting-edge bioconjugation techniques for antibodies, proteins, peptides, and other biomolecules.
• Demonstrated hands‑on experience in analytical characterization of conjugates with a strong analytical mindset.  Proficiency in purification techniques such as RP-HPLC, FPLC, SEC, and IEX.
• Able to work independently or in cross-functional team settings with minimal supervision.
• Adaptable and flexible, able to navigate shifting priorities and handle day‑to‑day challenges with professionalism and confidence in fast‑moving environments.
• Self‑motivated with strong interpersonal, organizational, and communication skills, and able to take a hands‑on approach in a dynamic, fast‑paced, and collaborative environment.

About Flagship Pioneering

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com

Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $126,000 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL103 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL103's good faith estimate as of the date of publication and may be modified in the future.