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

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell® Fusion, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior. Auto insurers, automakers, commercial mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day.

CMT is looking for a creative, collaborative, and highly motivated Machine Learning Intern to help develop applied machine learning capabilities using real-world mobility and behavioral data. This internship is ideal for someone who enjoys solving ambiguous problems, building practical ML workflows, working with messy real-world datasets, and translating technical findings into clear recommendations.

The intern will work on a 12-week applied ML project involving data exploration, labeling strategy, feature engineering, model development, evaluation, and stakeholder-facing analysis. The ideal candidate has strong Python skills, a solid foundation in machine learning, strong initiative, and the ability to make progress in open-ended problem spaces.

Responsibilities:

• Explore real-world mobility datasets and identify useful behavioral, temporal, contextual, and aggregate patterns
• Help define practical data labeling guidelines, quality criteria, and edge-case handling rules
• Build and validate datasets for supervised machine learning experiments
• Develop baseline and improved ML models using Python and standard data science workflows
• Perform feature engineering, model evaluation, error analysis, and iteration
• Assess model performance across relevant data segments and edge cases
• Summarize findings, limitations, risks, and opportunities for technical and product stakeholders
• Produce clear documentation, analysis reports, and final recommendations

Qualifications:

• Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Data Science, Machine Learning, Statistics, Engineering, Applied Math, or a related quantitative field
• Strong Python programming skills and comfort working with real-world datasets
• Solid understanding of supervised machine learning, feature engineering, classification metrics, train/test splits, and error analysis
• Experience with common Python data science libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or similar tools
• Strong analytical and problem-solving skills, with a bias toward initiative and ownership
• Clear written and verbal communication skills, including the ability to explain technical findings to non-technical stakeholders

Compensation and Benefits:

• Fair and competitive hourly rate based on education level
• Flexible scheduling options depending on role and responsibilities

Additional Perks:

• Feel great working to improve road safety around the world!
• Join one of our many employee resource groups including Black, AAPI, LGBTQIA+, Women, Book Club and Health & Wellness
• CMT will do all that is possible to support our employees and create a positive and inclusive work environment for all!

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.

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.

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?

The VP, Development Data Science will build and lead a cross functional data centric matrix to accelerate drug development, support regulatory submissions and guide the Real-World Data (RWD) / Real-World Evidence (RWE) function at Parabilis. This role is responsible for end-to-end strategy and execution of RWD/RWE and clinical data science to inform trial design, contextualize clinical results, support biomarker and translational work, and optimize site and patient selection.

The VP will partner closely with Clinical Development, Clinical Operations, Biostatistics, Translational/Computational Biology, Regulatory, and the broader Data Science & Engineering team to maximize the probability of success of our clinical programs.

• Strategy & Leadership
  • Define and own the Clinical Data Science strategy.
  • Serve as the senior Clinical Data Science leader and primary point of contact for RWD/RWE across programs aligned with portfolio and corporate objectives.
  • Represent Clinical Data Science on cross-functional governance and portfolio forums.
• RWD/RWE & Clinical Analytics
  • Design and oversee RWE studies to contextualize clinical trials, including synthetic/external control arms, patient matching, and trial emulation.
  • Use RWD to inform clinical trial design (eligibility criteria, endpoints, enrichment strategies), dose/regimen selection, and go/no-go decisions.
  • Contribute data science insights for feasibility and site selection, including epidemiology, patient journeys, referral patterns, and diversity/access.
  • Integrate RWD with internal clinical and biomarker data to support forward and reverse translation, target and indication strategy, and mechanism-of-resistance analyses.
  • Establish and maintain best practices in causal inference, comparative effectiveness, and time-to-event modeling relevant to RWE in oncology.
• Data Assets, Partnerships & Infrastructure
  • Identify, evaluate, and prioritize RWD sources (EHR, claims, registries, genomic/omic datasets, imaging, PROs) to support current and future clinical needs.
  • Lead collaboration and contracting with RWD providers and academic/industry partners in coordination with Commercial, Business Development, Legal, and Procurement.
  • Partner with Engineering and Data Science to define requirements for secure, scalable, compliant RWD infrastructure and analytic environments.
  • Ensure data quality, interoperability, and governance suitable for regulatory-grade analyses.
• Team Building & Management
  • Build and lead a high-performing Clinical Data Science team (e.g., RWE epidemiologists, clinical data scientists, etc).
  • Set clear objectives, provide regular feedback, and support growth and succession planning.
  • Foster a culture of scientific rigor, transparency, and effective collaboration with Clinical Development, Biostatistics, and other partners.
• Cross-Functional Collaboration & Communication
  • Work in an integrated way with Clinical and Development teams to define key questions and translate them into analytic and RWE plans.
  • Communicate complex methods, assumptions, and results clearly to clinical, technical, and executive stakeholders.
  • Support regulatory and payer/Health Technology Assessment interactions where RWE and clinical analytics contribute to program strategy (e.g., briefing documents, responses, meeting preparation).
  • Collaborate with Translational and Computational Biology to align biomarker and patient selection strategies with integrated clinical and RWD analytics.
• Governance, Quality & Compliance
  • Ensure RWD/RWE activities meet regulatory, ethical, and privacy standards (e.g., GCP, data de-identification and privacy requirements).
  • Implement documentation, reproducibility, and quality standards for Clinical Data Science analyses.
  • Monitor evolving external expectations for use of RWE in regulatory and payer settings and adapt internal practices accordingly.

What you’ll need to be successful:

• PhD, MD, PharmD, or MS in Epidemiology, Biostatistics, HEOR, Data Science, or a related quantitative field.
• 12–15+ years of experience in pharma/biotech, healthcare technology, or related sectors, with significant focus on RWD/RWE and clinical development; oncology experience strongly preferred.
• Proven track record designing and delivering impactful RWE studies to inform clinical, regulatory, or payer decision-making.
• Strong understanding of clinical trial design, biostatistics fundamentals, and translational/biomarker concepts, ideally in oncology or immuno-oncology.
• Demonstrated experience building, leading, and developing high-performing quantitative teams in a matrixed environment.
• Hands-on familiarity with major RWD types (EHR, claims, registries, genomic/omic datasets) and key vendors/platforms.
• Proficiency with modern analytic tools and programming environments (e.g., R, Python, SQL) and with guiding development of robust, reproducible analytic workflows.
• Excellent communication and influencing skills with the ability to engage effectively with clinicians, statisticians, senior leaders, and external partners.

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 $325,000-$380,000 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

Human Factors Engineer

At MORSE, we solve hard problems to field innovative technology to our customers in the US Department of Defense and the Intelligence Community. We are a company of smart people, who are easy to work with and passionate about making an impact for national security. Our work spans UAVs with precision delivery, novel AI capabilities, Test and Evaluation to make sure the AI solutions accomplish their intended missions, and advanced Decision Systems to arm the warfighter with data to make better, faster decisions to plan missions and have situational awareness into potential threats.

Job Summary

As a Human Factors Engineer, you will work with end users and stakeholders to assess the operational effectiveness and performance of Artificial Intelligence (AI) systems. As we perform Operational Test & Evaluation (OT&E), you will lead user engagement and knowledge elicitation studies to understand user requirements and define metrics to assess the effectiveness of Human-AI teaming in operational environments. You will use your knowledge of iterative design processes to regularly elicit feedback regarding the human-AI teaming experience to recommend best practices, including design mock-ups, for enhancing the user's operational effectiveness. You will also use your advanced data analysis skills to evaluate human-AI performance under different operational conditions to tailor AI technical solutions for specific operational scenarios and tempos.

Responsibilities 

• Perform Human-Machine Teaming Test and Evaluation (HMT T&E) of Artificial Intelligence

• Lead user engagement studies, knowledge elicitation sessions, human-in-the-loop assessments, and workflow analysis

• Identify appropriate human performance metrics to evaluate the system performance and effectiveness of Human-AI Teaming

• Perform quantitative and qualitative assessments of human performance with AI systems

• Develop UI mockups

• Liaison between data scientists, software developers, analysts and end users

• Perform descriptive and inferential statistics to characterize human performance

• Be familiar with a wide range of metrics to assess signal detection from a human performance as well as a machine-learning perspective

• Provide technical direction and leadership to small-mid sized teams

Skills and Requirements

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

• MS or PhD in Cognitive Psychology, Psychology, User Experience, Human Factors, Mathematics, Statistics, Engineering, or other related field

• 5+ years of professional experience 

• Experience with HMT, HMI, HSI, Human Factors, Human Performance, and Usability

• Experience engaging with end users and stakeholders

• Programming skills in Python

About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

Your Impact at LILA

We're building autonomous robotic systems that serve as the intelligent physical infrastructure of our Scientific Superintelligence Platform at Lila. To support our robotics research roadmap, we need to scale robot data collection to produce high-quality robot data, collected by humans, at scale, day after day while improving per-operator throughput, lowering churn, and keeping data quality consistent across every supervisor and shift

We're hiring an Operations Manager to own that scale-up end-to-end.

As Data Operations Manager, you'll own the day-to-day function that generates the training data powering Lila's robotic systems. That means managing the supervisors who run our data collection shifts, setting the conditions for consistent operator performance, and making sure every hour of work on the floor translates into high-quality, usable data for our research team.

This is a builder role. The team is early — a growing group of operators across two shifts — and the processes, metrics, and programs that will scale it are still being shaped. You'll design and own them. You'll report directly to the Robotics team and serve as the primary operational link between the floor and Robotics Research.

What You'll Be Building

• Run the operation: Own the day-to-day operation across all shifts. Set throughput targets, monitor adherence, debug when shifts under-deliver, and make weekly calls on staffing, scheduling, and task allocation
• Manage the team: You'll manage the supervisors who directly run our operators. Set clear goals, run a consistent performance loop, and grow the supervisory bench as shifts, and sites, expand
• Drive retention and engagement: Data collection is physical, repetitive, attention-heavy work. Design and continuously refine onboarding, training, performance incentives, recognition, and scheduling so operators stay engaged and the bar keeps rising. Approach this with a product mindset: hypothesize, ship, measure, iterate
• Own throughput and quality metrics. Set targets, build the dashboards, and run the review cadence that make performance visible across the team. Reduce reject rates, compress reset time, and increase usable hours per shift
• Plan capacity: Translate research priorities into concrete operational plans — operator allocation, supervisor coverage, equipment requirements, and risk. Forecast throughput, flag potential misses early, and re-plan as priorities evolve
• Scale the footprint: Partner with facilities, recruiting, and leadership to expand the operation across additional shifts and, in time, additional sites. Maintain an operational playbook that makes opening each new shift or site repeatable rather than bespoke
• Be the bridge to research: Meet with the research team to understand upcoming priorities: which tasks, which embodiments, what success looks like. Translate those needs into shift plans, and surface friction (poor reset ergonomics, ambiguous instructions, unreliable hardware) before it costs the team hours

What You’ll Need to Succeed

• 4+ years of operations or program management experience, including direct people management
• A track record of running shift-based, throughput-driven operations — ****warehousing, manufacturing, contact centers, data labeling, clinical ops, field operations or comparable
• Demonstrated success reducing churn or improving retention in a frontline workforce: We want to hear the specifics: the baseline, the intervention, and the outcome
• Comfort with metrics: You should be able to look at our shift summary, immediately spot what's interesting, and know what to ask for next
• Builder mindset: This is a function being built, not inherited. Some processes are still taking shape, and we are looking for the right person who sees that as an opportunity to grow and deliver
• Strong written communication — ****you will be the connection between the floor and research and engineering teams, and much of that work happens in documentation
• Willingness to be on-site and on-floor: This role depends on presence and proximity to the team

Bonus Points For

• Experience managing managers or building a supervisor layer from scratch
• Background in robotics, autonomous systems, or physical AI data collection
• Experience scaling a frontline team from under 20 to 100+
• Familiarity with workforce management software, shift-scheduling tooling, or QA workflow tools
• Background in industrial engineering, operations research, or a related quantitative field

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.

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

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

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.

What You'll Be Building

• Agentic AI for science: Systems that perform sequential decision‑making and multi‑step reasoning to solve domain‑specific problems.
• Workflow/code generation: From natural language intent to typed, executable steps for lab instruments.
• Evaluation & reliability: Benchmarks, test suites, and telemetry to measure capability and quantify progress toward scientific goals.

What You’ll Need to Succeed

• PhD or Masters in a quantitative discipline (e.g., Computer Science, Physics, Mathematics, Engineering) with a strong background in machine learning and one domain of science (e.g. biology or materials science).
• Strong grasp of LLMs and agent architectures (planning, tool use, structured function calling, code generation) and how to adapt them to domains.
• Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) and experience implementing scalable solutions for complex tasks.
• Comfort collaborating across disciplines and interfacing with simulations and real lab systems.

Bonus Points For 

• Building long‑horizon agents or RL for control/decision‑making; experience with model‑based or offline RL.
• Designing domain‑specific benchmarks and evaluation harnesses for complex scientific tasks.
• Digital‑twin development, calibration, and sim‑to‑real transfer.
• Publications or open‑source contributions in AI for science (especially publications in top-tier conferences like NeurIPS, ICML, AAAI, ICLR).

Location

San Francisco, CA or Cambridge, MA (Hybrid and On-Site available depending on team needs).

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

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

What if… you could pioneer a new approach to designing life’s most essential molecules?

FL116, backed by Flagship Pioneering, is an early-stage biotechnology company transforming the way biomolecules are synthesized. Our innovative platform has the potential to transform how critical research, diagnostic, and therapeutic molecules are manufactured. We are seeking passionate problem solvers ready to make a profound impact on biotechnology and therapeutic innovation.

Position Summary

We are seeking a motivated, detail-oriented, and intellectually curious Research Associate or Senior Research Associate to join our Chemical Biology team. This role is centered on applying chemistry to solve complex biological problems, interrogating and controlling enzyme-driven biomolecular synthesis through a mechanistic and molecular lens.

You will execute high-throughput experiments to probe enzyme–substrate interactions, characterize biomolecule products, and contribute to the development of robust, scalable assays that power our platform. The ideal candidate appreciates the dynamic chemical nature of biological systems and is excited to manipulate and measure biology at the molecular level.

This is an exciting opportunity to build deep expertise at the interface of chemistry and biology within a fast-paced, collaborative startup environment. You are a hands-on experimentalist who thrives in execution-focused, pipeline-driven work and is eager to grow alongside a rapidly evolving technology platform.

Key Responsibilities

• Execute high-throughput experiments to characterize enzyme–substrate and enzyme–product interactions, with a focus on understanding underlying chemical mechanisms
• Apply chemical principles to modulate and interrogate protein function, reactivity, and biomolecular synthesis pathways
• Perform biomolecular product characterization using analytical and separation techniques (e.g., gel electrophoresis, TapeStation, HPLC, plate-based assays)
• Support the development, optimization, and scaling of biochemical and enzymatic assays with an emphasis on quantitative, reproducible readouts
• Generate, analyze, and interpret experimental datasets to extract mechanistic insight and inform pipeline progression
• Collaborate closely with cross-functional teams, including Enzyme Science and Assay Development, to integrate chemical insight into broader platform workflows
• Maintain rigorous experimental documentation and contribute to protocol development and knowledge sharing across the team

Qualifications

• B.S. or M.S. in Chemistry, Chemical Biology, Biochemistry, Biotechnology, or a related discipline with a strong foundation in chemical principles applied to biological systems
• 2+ years of relevant laboratory experience (industry or academic)
• Hands-on experience applying chemistry to biological systems, including enzymatic assays, biomolecule manipulation, or reaction-based workflows
• Strong foundation in protein chemistry, enzymology, or biomolecular interactions
• Proficiency in core laboratory techniques including pipetting, gel electrophoresis, and quantitative assay execution
• Demonstrated ability to generate high-quality, reproducible data and perform rigorous data analysis
• Experience working in fast-paced, collaborative laboratory environments

Preferred Qualifications

• Experience with analytical and separation techniques such as HPLC, capillary electrophoresis, TLC, or plate-based detection systems
• Exposure to bioorthogonal chemistry, chemical modification of biomolecules, or mechanistic enzymology
• Familiarity with nucleic acid or protein characterization platforms (e.g., TapeStation or similar technologies)
• Experience contributing to assay development, optimization, or high-throughput workflows
• Experience preparing samples for NMR
• Familiarity with automation platforms for high throughput screening

Who You Are

Innovative Pioneer: You are excited by the opportunity to explore new scientific frontiers and apply chemical thinking to unlock biological complexity.

Collaborative Contributor: You work effectively across teams, communicate clearly, and value shared success in a highly interdisciplinary environment.

Inventive Problem Solver: You approach challenges with curiosity and creativity, using first-principles thinking to develop elegant experimental solutions.

Mission-Driven Individual: You are motivated by the opportunity to fundamentally change how biomolecules are synthesized and to impact human health and biotechnology.

Motivated Learner & Emerging Professional: You are eager to deepen your expertise in chemical biology, take ownership of your work, and grow into a highly capable scientist within a startup environment.

Values and Behaviors:

Flagship is an experiment in institutional, entrepreneurial, and innovation practiced in the context of a small company with an insurgent mindset. We are seeking individuals with an entrepreneurial spirit, strong communication skills, and comfort in working in and contributing to a dynamic and cross-functional team environment.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, we encourage you to 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. The level of the role will be commensurate with the education and years of experience of the identified candidates.

Flagship Pioneering and our ecosystem companies are 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.

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 $81,000 - $107,250. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL116 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL116's good faith estimate as of the date of publication and may be modified in the future.

Flagship Pioneering is a biotechnology company that invents and builds platform 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 and sustainability exponentially accelerate scientific progress in areas ranging from cancer detection and treatment to nature-positive agriculture.  

What sets Flagship apart is our ability to advance biotechnology by uniting life science 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.

Why Flagship?
At Flagship Pioneering, YOU get: inspiring leadership, great company culture, competitive compensation packages, best in class benefits, generous PTO, beautiful office space stocked with unlimited snacks and free lunch delivered daily, and impactful work with endless career growth.

The Position: 

The Sr. Manager or Associate Director of Business Development, depending on experience, will be a core part of the team responsible for strengthening our business through helping capture and implement learnings about the biopharma deal environment by operationalizing BD processes and analytics for Flagship and our ecosystem companies. This role will report to the Director of BD and will be critical in accelerating the growth of the FSP BD team. This individual should have a passion for working at the intersection of science and business and have an analytical mindset who thrives in a fast-paced, dynamic, and deadline driven environment. This individual should have a can-do attitude, be open to change and be excited about understanding the biopharma business development landscape. 

Key Responsibilities: The successful candidate will work both independently and as part of a collaborative team to: 

• Actively participate in the analytics of an effective and efficient business development effort/team 
• Lead pharma profiling in terms of characterizing their positioning in the partnering landscape, understanding their structure and decision-making process, capturing the knowledge gained from deepening FSP relationships and driving additional knowledge capture on behalf of FSP and our companies 
• Own pharma contact interface and leverage for BD analytics 
• Prepare opportunity assessments with scientific/portfolio rationale, partnership framework and financial assessment, analysis of competitive landscape and comparable deal terms 
• Build internal champions to amplify FSP BD reach, including for biopharma account management and ask KOLs for data review 
• Support deal activities including campaign design, outreach, tracking, deal structure design, term sheet assessment, research planning 
• Track progress, including coordinating the definition and reporting of the KPIs, as well as leading periodic health checks to monitor the strength and effectiveness of the partnership 
• Build strategy for and communication of intelligence acquisition gained through medical conference attendance, analyst report review 
• Partner with CBDO to own and share history and best practices across the ecosystem   

Preferred Qualifications: 

• 2-5 years life sciences experience in a business development function in a biotechnology/pharmaceutical company, Life Science Consulting form or biopharma investment banking 
• Knowledgeable about trends and technologies in biopharmaceutical R&D and partnering 
• Comfort in the start-up environment, passion for understanding emerging data and navigating ambiguity in a dynamic environment 

Basic Qualifications: 

• BS or other graduate degree in the life sciences required 
• Understanding of biopharmaceutical R&D, the drug development process, and the role and processes of business development 
• Excellent analytical/quantitative, conceptual problem-solving, organizational and time management skills and are comfortable working independently 
• Clear communicator in writing and speech and creative in terms of visual presentation of trends and data 
• Strong attention to detail 

Flagship Pioneering and our ecosystem companies are 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.

#LI-TD1

The salary range for this role is $128,000 - $203,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Flagship Pioneering currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Flagship Pioneering's good faith estimate as of the date of publication and may be modified in the future.

Vesalius Therapeutics is seeking a computational biologist with 5+ years of experience in high-dimensional data analysis to join our team. You will report to the Head of Data Science and develop and apply state-of-the-art statistical methods to deliver actionable insights from our population scale iPSC-based high-throughput phenotyping platform. You will bring a solid foundation in applied statistics; high-performance, scalable, and reproducible scientific code; and molecular, cell, or tissue biology. You will serve also as a subject matter expert on statistical analysis and software development, mentoring junior data scientists and advising stem cell scientists and biologists. You will work both independently and in matrixed teams with stem cell scientists, biologists, statistical geneticists, and machine learning scientists. This is the opportunity to redefine common diseases using genetic and phenotypic data at an unprecedented scale and make critical advances in developing new therapeutics to address unmet need!

What You’ll Do:

• Deliver biological insights into cellular networks, patient biomarkers, and iPSC-based physiological models and champion decisions and next steps
• Write and deploy high-performance code/pipelines for large-scale computation
• Identify relevant external data sets and new opportunities/needs for internal data generation
• Integrate closely with stem cell and biology teams on experimental design, hypothesis generation, and data analysis
• Provide technical expertise and mentorship on statistics and computation to junior data scientists and stem cell and biology teams
• Communicate to both technical and non-technical audiences clearly both orally and in writing

What You’ll Bring:

• PhD. in Statistics, Biostatistics, Computer Science, or Mathematics
• 5+ years of industry experience analyzing high-dimensional datasets
• Knowledge of quantitative genetics in human or model organisms a plus
• Demonstrated expertise in computation and biology supported by publications or presentations
• Demonstrated proficiency in a relevant programming language (Python, R, etc.) supported by a public Github repository
• Experience developing novel models, algorithms, or software implementations a plus
• Strong communication skills in writing and speaking

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 $146,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Vesalius Therapeutics currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Vesalius Therapeutics'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 first Computational Genomics hire, who will conduct crucial research that will form the basis of the company’s scientific platform. As an early stage hire, you will operate with significant ownership, shaping analytical strategy from first principals, intersecting the fields of genomics, statistical genetics and statistical modeling. The role includes responsibility of the end-to-end delivery of computational research projects, including project design, implementation, interpretation and reporting results to senior leadership. We are looking for someone who is resourceful, is open to a rapidly changing, agile environment and has bias to action. The ideal candidate combines deep technical rigor with a growth mindset, pays attention to detail, and has a deep-rooted desire to achieve excellence. Being collaborative is key – the environment is an early stage startup, where all members of the team need to work closely together to break new ground in science.

Key Responsibilities:

• Deliver computational research projects with a high degree of autonomy, including project design, implementation, interpretation and reporting results to senior leadership
• Collaborate with cloud engineers to set up the required infrastructure to process and store genomics datasets
• Integrate multiple NGS data types into coherent analyses, going from raw input files to variant calls and higher level analyses
• Develop probabilistic and Bayesian models that rigorously incorporate priors, uncertainty, and missing data to inform decision-making
• Interact with external advisors, leveraging their inputs and building high-quality relationships

Requirements:

• Ph.D. in biology, statistics, genetics, computational biology or a related quantitative discipline with 5+ years of relevant post-academic or industry experience with an excellent research track record
• Deep expertise in the analysis of genomics data derived from Illumina sequencing platforms (expertise with additional sequencing technologies is a plus)
• Experience processing next-generation sequencing data end-to-end, from raw reads through alignment, QC, and variant calling
• Experience integrating and jointly analyzing multi-modal sequencing datasets, including DNA and RNA
• Expertise in statistical genetics, computing polygenic risk scores using published methods and adapting or extending these methods for novel applications
• Expertise in building probabilistic statistical models that explicitly account for uncertainty, prior information, and incomplete observations
• Comfort operating in fast-moving, ambiguous startup environments with high ownership and accountability

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 $146,000 - $209,000. 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.

Build Models Where None Exist Yet.

At Flagship Pioneering, we create companies from first principles. Within Flagship Labs, small founding teams define new technical theses, test them rapidly, and build ventures around breakthrough ideas.

We are forming a machine learning team inside a newly launched venture, Flagship Labs 120. Our work focuses on extracting latent structure from information-rich measurements of complex physical systems—often requiring mechanism-informed modeling, thoughtful inductive bias design, and principled approaches to inverse problems.

This is a zero-to-one role focused on modeling innovation rather than routine optimization. You’ll design, prototype, test, and refine new approaches that help define the technical foundation of a platform from day one.

What You’ll Do

• Develop and iterate on ML models for complex measurement data, from representation design through validation
• Design objectives and architectures that respect known constraints, symmetries, or latent structure in the data
• Explore and compare modeling strategies, balancing strong baselines with more experimental approaches when appropriate
• Investigate model behavior and failure modes to improve robustness and interpretability
• Collaborate closely with experimental and technical teammates to align modeling with data generation
• Contribute to shaping the long-term ML strategy and technical direction of a new venture

Who You Are

You may come from physics, applied mathematics, engineering, computer science, or another quantitative field.  You have hands-on experience developing machine learning models—ideally in deep learning, representation learning, probabilistic modeling, or related areas. You are comfortable implementing and modifying models, training them end-to-end, and working directly with real data.

You likely:

• Think algorithmically and reason from underlying structure
• Are comfortable adapting or extending model architectures when needed
• Have built and debugged meaningful ML systems or research prototypes
• Enjoy operating in dynamic, early-stage environments
• Read papers, build prototypes to test ideas, and translate concepts into working systems

What matters most is your ability to reason across data, models, and the systems they represent.

Technical Background

Required

• Strong hands-on experience building and training modern ML models
• Fluency in Python and at least one major ML framework (e.g., PyTorch or equivalent)
• Experience working with real-world or experimentally generated data
• Ability to design, run, and interpret ML experiments
• Comfort working in practical development environments (e.g., cloud infrastructure, experiment tracking, reproducible workflows)

Helpful

• Experience with inverse problems, latent-variable inference, or structured generative modeling (e.g., diffusion or flow-based methods)
• Familiarity with geometric or symmetry-aware architectures
• Experience incorporating physical or structural constraints into learning systems
• Experience working with time-series or high-dimensional signal data
• Exposure to biology, chemistry, physics, or related sciences

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.

The salary range for this role is $130,000 - $230,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL120 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL120's good faith estimate as of the date of publication and may be modified in the future.

Position Summary

We are seeking a Scientist to join a dynamic team applying computational and data-driven approaches to design novel antigens and evaluate vaccine responses. At Apriori Bio, we have built our biology-enabled AI/ML platform Octavia™ to map viral fitness landscapes, predict immune escape trajectories, and design vaccines to elicit an optimal protective response to future challenges. The successful candidate will contribute to the development and application of computational methods—including structural modeling, machine learning, and statistical inference— that build on Octavia™ insights to support the company’s vaccine design efforts. Experience working with protein engineering and immunological datasets is valuable, as is interest or training in high-throughput functional genomics, virology, or vaccinology.

The Scientist will work closely with both computational and experimental colleagues to interpret results, generate hypotheses, and support antigen design. This role is ideal for scientists eager for a unique opportunity to learn and innovate within an interdisciplinary, fast-paced startup environment.

Key Responsibilities

• Use high-dimensional datasets (e.g., mutational scanning, NGS-based phenotypic screens) and computational approaches—including structural modeling, sequence analysis, and machine learning—to support antigen and immunogen engineering
• Apply and refine computational models that integrate screening data with structural and sequence-based features to guide biomolecule engineering
• Generate hypotheses and design analyses that inform evaluation of novel immunization strategies (in partnership with experimental teams)
• Identify, evaluate, and curate external datasets relevant to vaccine design and antigen optimization
• Develop reproducible computational tools and pipelines for data-driven product design that can be integrated into broader platform workflows
• Collaborate with engineers, computational scientists, and experimentalists to execute project goals and ensure smooth integration of computational findings
• Work with immunology and characterization teams to interpret vaccine immunogenicity using next-generation immune monitoring and antibody profiling tools
• Clearly communicate results and insights to colleagues across scientific and cross-functional teams
• Tackle difficult scientific problems with creativity and resilience while iterating quickly as new data emerges
• Take ownership of complex, open-ended scientific questions, driving analyses forward through ambiguity while balancing speed, rigor, and collaborative problem-solving

Basic Qualifications

• Ph.D. in bioengineering, immunology, computational biology, or a related field (or equivalent research experience)
• Experience applying data-driven protein engineering methods to predict and affect protein function, including structural and sequence-based machine-learning approaches
• Experience or training in antigen design leveraging vaccine immune response readouts
• Solid statistical and quantitative foundation, with the ability to translate complex biological datasets into actionable insights
• Strong scientific programming skills (Python preferred) and familiarity with best practices in reproducible scientific computing
• Experience working with high-throughput biological data or NGS-based assays, including modeling and statistical analysis
• Experience using version control and collaborative coding workflows

Preferred Qualifications

• Experience in vaccine design
• Experience with deep learning approaches
• Exposure to antibody characterization, immune profiling, or immune repertoire analyses
• Experience with NGS data pipelines, from processing to interpretation
• Familiarity with cloud or distributed computing environments
• Familiarity with storage, analysis and transformation of large tabular datasets and relational databases
• Laboratory experience in molecular biology, biochemistry, or immunology (a plus, not required)

About Flagship

Flagship Pioneering is a biotechnology 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. 

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 $115,000 - $165,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Apriori Bio, Inc. currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Apriori Bio, Inc.'s good faith estimate as of the date of publication and may be modified in the future.

Vesalius Therapeutics is seeking a computational biologist with 5+ years of experience in high-dimensional data analysis to join our team. You will report to the Head of Data Science and develop and apply state-of-the-art statistical methods to deliver actionable insights from our population scale iPSC-based high-throughput phenotyping platform. You will bring a solid foundation in applied statistics; high-performance, scalable, and reproducible scientific code; and molecular, cell, or tissue biology. You will serve also as a subject matter expert on statistical analysis and software development, mentoring junior data scientists and advising stem cell scientists and biologists. You will work both independently and in matrixed teams with stem cell scientists, biologists, statistical geneticists, and machine learning scientists. This is the opportunity to redefine common diseases using genetic and phenotypic data at an unprecedented scale and make critical advances in developing new therapeutics to address unmet need!

What You’ll Do:

• Deliver biological insights into cellular networks, patient biomarkers, and iPSC-based physiological models and champion decisions and next steps
• Write and deploy high-performance code/pipelines for large-scale computation
• Identify relevant external data sets and new opportunities/needs for internal data generation
• Integrate closely with stem cell and biology teams on experimental design, hypothesis generation, and data analysis
• Provide technical expertise and mentorship on statistics and computation to junior data scientists and stem cell and biology teams
• Communicate to both technical and non-technical audiences clearly both orally and in writing

What You’ll Bring:

• PhD. in Statistics, Biostatistics, Computer Science, or Mathematics
• 5+ years of industry experience analyzing high-dimensional datasets
• Knowledge of quantitative genetics in human or model organisms a plus
• Demonstrated expertise in computation and biology supported by publications or presentations
• Demonstrated proficiency in a relevant programming language (Python, R, etc.) supported by a public Github repository
• Experience developing novel models, algorithms, or software implementations a plus
• Strong communication skills in writing and speaking

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 $146,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Vesalius Therapeutics currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Vesalius Therapeutics's good faith estimate as of the date of publication and may be modified in the future.

Are you driven by data, inspired by innovation, and eager to shape the future of insurance?

Join a fast-growing Canadian P&C insurer where you'll play a pivotal role in advancing our Actuarial Services function. We're building on a solid foundation—powered by cutting-edge technology, a robust enterprise data analytics team, and bold investments in AI. With this groundwork in place our talented team is now focused on scaling and refining our capabilities.

We're looking for bright, analytical minds to help bring our strategy to life. If you're passionate about solving complex problems and want to explore Pricing, Underwriting, and Claims, we want to hear from you.

Senior Data Scientist

We're looking for a Senior Data Scientist to join our growing team and build the next generation of predictive analytics solutions. In this role, you won’t just be crunching numbers, you’ll be using machine learning (ML) and artificial intelligence (AI) models to transform raw data into powerful insights that drive our business forward.

This is an opportunity to directly contribute to our core operations, working alongside a supportive team who are invested in your growth. If you have a passion for data and a desire to see your work make a tangible impact, this role is for you.

What you'll do:

• Deliver value through data-driven algorithms and models: You will apply the right mix of ML and AI to solve high-impact business problems. You’ll partner with stakeholders to select and defend the best model architecture and explainability approaches to balance performance, interpretability, and trade-offs.
• Embed ML/AI into core business capabilities: You will build deep expertise in P&C insurance workflows and translate that knowledge into practical ML/AI-powered analyses, decision tools, and visualizations that improve how work gets done.
• Partner with stakeholders to ensure adoption, value, and model integrity: You’ll align with stakeholders on goals and success metrics, then pressure-test solutions against real constraints to ensure they’re feasible and valuable. You will communicate your insights and recommendations with clarity and confidence to both technical and non-technical audiences.
• Invest in Your Future: We're committed to your professional development. You'll engage in project-specific research to continually grow your skills and have the unique opportunity to collaborate with our Claims and Finance departments.

 What You’ll Need to Succeed

• Education: You have a master’s degree in a quantitative or technical discipline
• Experience: You have 3–5 years of experience in an ML/AI development role, with experience deploying ML / AI models into production and associated governance procedures.
• Technical Skills: You have a broad understanding of modern ML architectures, familiarity with cloud and ML platforms. You have strong Python programming skills and experience with various ML libraries.
• Core Competencies: You have excellent analytical, quantitative, and critical thinking skills. You are highly analytical and use your communication and collaboration skills to engage with stakeholders to solve problems.

If you're ready to be a core part of our mission and make a tangible impact from day one, we want to hear from you.

#LI-Hybrid

The expected base salary range for this position is $79,500 - $129,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

Gore Mutual is proud to offer a comprehensive total rewards package which includes extended health and dental benefits, disability insurance, retirement plan matching, paid time off, recognition and perk programs.

About the team

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.  

About the role

In this role you will work on applying SOTA research and conduct your own research to develop novel methodologies to solve a large variety of challenging problems in Advertising related to conversion modeling aligned with attribution methodologies/models, calibration, dynamic creative generation and optimization, forecasting and timeseries modeling, yield and margin optimization and Experimentation for A/B and multivariate testing. 

We’re looking for a strong technical leader with a solid grasp of core statistical techniques and deep experience in SOTA Deep Learning discriminative and generative models. 

What you will be doing

• Applying existing and conducting your own research to build SOTA Deep learning discriminative models and build generative models to create image and video ads geared towards optimizing performance.
• Stay at the forefront of advancements in related areas. 

We're excited if you have

• PhD in quantitative disciplines such as CS, Statistics, Applied Math or a related field.
• Extensive experience in applied research using statistical and deep learning techniques.
• Published paper(s) on deep learning models for Advertising or related areas.
• Excellent communication and collaboration skills. 
• Experience in the Advertising domain (preferred)
• Contributions to open-source ML projects (preferred)

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasizes teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Redwood City, CA:

• Senior Scientist I, Machine Learning: $257,400 - $330,000
• Senior Scientist II, Machine Learning: $290,900 - $373,000
• Principal Scientist, Machine Learning: $330,800 - $424,100

The salary range for San Diego, CA:

• Senior Scientist I, Machine Learning: $239,500 - $307,000
• Senior Scientist II, Machine Learning: $262,100 - $336,000
• Principal Scientist, Machine Learning: $312,100 - $400,100

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

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.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasises teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Senior Scientist I, Machine Learning: £115,600 - £152,100
• Senior Scientist II, Machine Learning: £131,900 - £173,500
• Principal Scientist, Machine Learning: £173,700 - £228,600

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

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.

#LI-NN1

What You Will Contribute to Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Scientist I, Machine Learning: £74,900 - £98,500
• Scientist II, Machine Learning: £107,900 - £142,000
• Senior Scientist I, Machine Learning: £115,600 - £152,100

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

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.

#LI-NN1

What You Will Contribute To Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source softwar

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

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

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.

#LI-NN1

The Role:

The Senior Director, Clinical Pharmacology will lead Nuvalent’s clinical pharmacology strategy across all development programs, including late‑stage registrational efforts and emerging early‑phase assets. This leader will guide dose optimization, exposure–response modeling, regulatory strategy, and clinical pharmacology components of NDA submissions.  

Responsibilities:

• Serve as the clinical pharmacology lead and develop and execute strategies to support Phase 1, registrational, and post‑marketing studies, including designing and leading clinical pharmacology studies.
• Drive the integration of PK, PD, safety, and efficacy data to inform dose selection, dose modification, and labeling recommendations.
• Lead clinical pharmacology contributions to INDs, CTAs, IBs, and NDA submissions.
• Represent clinical pharmacology in interactions with FDA and other global regulators, supporting discussions related to dose justification, pediatric waivers, safety margins, and DDI strategies.
• Partner closely with DMPK, Non-clinical Toxicology, Clinical Development, Biostatistics, CMC, and Regulatory Affairs to ensure cohesive end‑to‑end development plans.
• Oversee population PK modeling, PK/PD modeling, and exposure–response analyses for efficacy and safety.
• Guide quantitative pharmacology approaches supporting optimal dosing in patients.
• Build and mentor a growing clinical pharmacology function as Nuvalent transitions from clinical‑stage to commercial‑
• Contribute to portfolio prioritization, scenario planning, and long‑range clinical development strategy.

 Competencies:

• Demonstrated ability to collaborate across matrixed, cross-functional teams in a fast-paced environment.
• Proven ability to manage multiple projects simultaneously with attention to timelines and detail.
• Strong communication and interpersonal skills; build trust and foster relationships internally and externally.
• Able to work independently, take initiative, and adapt quickly to evolving priorities.
• Recognized leader who exhibits effective communication, emotional intelligence, and influencing skills, within a matrix operating environment.
• Demonstration of strategic thinking and high-level planning while also balancing the ability to manage and execute operational details.
• Ability to effectively manage multiple projects with competing priorities.

  Qualifications:

• D., Pharm.D., or M.D. with specialization in Clinical Pharmacology, Pharmacokinetics, Pharmaceutical Sciences, or related discipline.
• 12+ years of experience in clinical pharmacology within biopharma, including leadership in oncology or small‑molecule drug development.
• Proven track record supporting registrational‑stage programs and authoring components of regulatory submissions (INDs, NDAs/MAAs).
• Prior work with kinase inhibitors, and oncology therapies strongly preferred.
• Familiarity with late‑phase trial design and commercial launch preparation.

 Additional Information:

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

The targeted salary range below 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

About the Role:

Stylus Medicine is seeking an innovative, intellectually curious and team-oriented Principal Scientist to support our large serine recombinase (LSR) engineering platform. This individual will provide high-resolution efficacy and specificity analysis to advance our pipeline as well as support onboarding of new preclinical assays for regulatory submissions, ensure accuracy of our analysis pipelines and translate our wet lab experiments into computational insights that will enable engineering of our next generation LSRs.

Key Responsibilities & Accountabilities:

• Lead the analysis of NGS data from LSR experiments (like amplicon, hybrid capture, and long-read sequencing) to quantify target efficiency and specificity
• Build integrated workflows to annotate and characterize target sites by synthesizing proprietary datasets with large-scale public genomic databases
• Design, implement, and scale robust computational pipelines for multi-omics analysis
• Collaborate closely with the Screening, Genome Engineering, and Protein Engineering teams to design experiments and interpret results
• Develop and maintain internal databases and infrastructure to ensure experimental results are accessible, reproducible, and actionable
• Contribute to patent filings, regulatory submissions, and scientific publications

Qualifications & Skills:

• PhD with 5+ years or Master’s with 10+ years (or Bachelor’s with 12+ years) of industry experience in Computational Biology, Bioinformatics, or a related quantitative discipline.
• Strong expertise in experimental design, data processing, statistical analysis, and NGS data analysis
• Expert-level proficiency in Python and/or R, with extensive experience using data science libraries (e.g., Pandas, NumPy, Bioconductor)
• Experience with cloud computing platforms for large-scale data processing and with workflow management systems
• Excellent organizational, communication, and documentation skills, with demonstrated ability to work effectively in collaborative, interdisciplinary environments
• Strong scientific critical thinking skills, including the ability to evaluate approaches, synthesize complex data, and provide actionable recommendations
• Proven track record of working successfully across cross-functional teams with proactive communication and timely delivery

Pay Range: $180,000 - $195,000

Warning: Fraudulent Job Adverts Beware of fraudulent activities claiming to represent Insurify. We are not associated with any entities soliciting personal information or payment. The safety of our job seekers is a top priority, and we actively work to prevent such incidents. Insurify will never request sensitive information or payment during the hiring process. Be cautious of text-only interviews, interviews conducted through Microsoft Teams, or suspicious offer letters. 

Why us? 

Insurify is one of America’s fastest-growing MIT FinTech startups and has been recognized as one of Inc. 5,000’s fastest-growing private companies in America in 2025, 2024, 2023, 2022 and 2021, Forbes Fintech 50 List for 2023, 2022, and 2021, Forbes Next Billion Dollar Startups of 2022 global and Top 100 InsurTech company. We’re changing the way millions of people compare, buy and manage insurance with artificial intelligence, technology, and superior product design.

Our company vision is to be recognized as the preeminent and most trusted digital agent for insurance comparison, purchase, and management. Our team is critical to achieving our vision and fostering the right culture is essential to our team’s success.

Join us if you like

• $1.3 Trillion market opportunity
• MIT alumni founders
• Female-led startup
• $130M total funding
• Strong leadership team with experience from many successful startups around the world

Insurify is looking for several Business Data Analysts to be a part of a rotational analytics program. Analysts will have the opportunity to work within our Marketing, Analytics, and Engineering teams to solve cross-functional, high velocity, high impact analytics problems and scale the business using data.This will include a mix of business analytics, analytics engineering, and data science using SQL and Python.

This role is about using data to make our company better across all areas of the business, so we want people who are excited to tackle a wide range of structured and unstructured problems using data! Solutions do not come in neat boxes.

Sample projects:

• Analyze a novel dataset to recommend areas for the business to improve
• Operate and improve a core data product optimizing for multiple competing KPIs 
• Build new data pipelines to support tracking of a new business initiative
• Innovate data modeling and data presentation to drive business understanding
• Improve prediction accuracy of our customer acquisition machine learning bidding algorithms
• Build reports and dashboards to help power the company’s decision making
• Do customer segmentation analysis to discover where to improve Insurify products

Key Skills

• Bachelors in computer science, analytics, economics, or other STEM major required. Masters preferred.
• Strong quantitative and programming skills with a product-driven sensibility.
• Quick learning ability and a drive suitable for the startup hustle.
• A friendly cooperative disposition and an eagerness to learn
• Python (preferred) or R.
• A positive team player with a solid work ethic who is ready to pivot between projects, learn from mistakes, always move forward, and help build the next big thing in insurance!
• Expertise in and real-world experience with SQL.

Nice to have skills

• Website tracking. HTML, Javascript, website tracking analytics, pixel and event tracking
• Familiarity with production data systems, big data, Apache Spark, dbt, and SQL
• R, C++, C#, Javascript
• Any domain specific experience relevant to Marketing, SEO, Retention, Product
• Knowledge of statistics
• Experience in data analysis in consumer / retail / e-Commerce / SaaS