What You Will Contribute To Altos

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

Responsibilities

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

Who You Are

Minimum Qualifications

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

Preferred Qualifications 

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

The salary range for Cambridge, UK:

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

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

#LI-NN1

For UK applicants, before submitting your application:

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

Company Description 

FL121 is a privately held biotechnology company engineering nature to build next generation therapeutics. By harnessing naturally occurring chemistry and pairing it with sophisticated high-throughput screening technology, we will unlock the future of de novo drug design via curated data creation and model training.  

Role Overview 

We are building a therapeutic discovery platform centered on biosynthetically-derived chemistry and advanced analytical readouts. This role will provide direct experimental support to the platform’s Build arm: executing cloning, expression, and purification workflows with a high degree of independence and rigor. The Sr. RA will be a hands-on contributor to day-to-day bench operations and will help maintain the throughput and data quality needed to drive rapid, data-grounded decisions. 

Key Responsibilities 

• Execute molecular cloning workflows end-to-end using modern assembly methods (Gibson, T2S/Golden Gate, and related approaches); maintain accurate plasmid maps, sequence records, and construct libraries. 

• Express and purify recombinant proteins in bacterial systems; independently troubleshoot yield, solubility, and purity issues across the full workflow from culture through final polishing steps. 

• Maintain rigorous records of experimental conditions, reagent lots, and QC data; contribute to reproducible, well-documented protocols and sample tracking practices that support downstream analytical and screening steps. 

• Partner with senior scientists and cross-functional teams to deliver high-quality material inputs that enable platform proof-of-concept experiments; communicate results and blockers clearly and proactively. 

Required Skills and Experience 

• Demonstrated proficiency in modern DNA assembly methods (Gibson Assembly, Type IIS/Golden Gate, and related scarless cloning strategies); able to take a construct from design to sequence-verified clone independently. 

• Hands-on experience with recombinant protein expression (E. coli required; additional systems a plus) and purification by affinity chromatography and related downstream steps; able to assess purity and integrity via analytical methods. 

• Familiarity with standard analytical tools (chromatography, gel electrophoresis, UV absorbance) and biochemical assays (ELISA, BLI) for protein and DNA characterization 

• Track record of executing multi-step molecular biology workflows end-to-end with minimal supervision; strong attention to detail in protocol execution and data recording. 

• Senior Research Associate: Typically requires a BS degree in a relevant scientific discipline with 5+ years of industry experience; or a Master’s degree in a relevant scientific discipline with 3+ years of experience. Academic experience including co-ops and internships counts toward degree requirements and not work experience. 

Preferred Experience 

• Experience supporting or interfacing with mass spectrometry-based readouts. 

• Experience with laboratory automation platforms, LIMS/sample tracking systems, or basic scripting (Python/R) for data organization and analysis. 

What it Takes to Succeed in This Role 

• Comfort in ambiguity; can move between strategy and execution. 

• Creative and rigorous in experimental design, documentation, and data interpretation. 

• Collaborative communicator; gives/receives feedback effectively. 
• Grit and agility in fast-moving environments. 

Values and Behaviors 

We are seeking individuals with an entrepreneurial spirit, strong communication skills, and comfort working in and contributing to a dynamic and cross-functional team environment. The level of the role will be commensurate with the education and years of experience of the identified candidate. 

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 $81,000 - $107,250. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL121 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL121's good faith estimate as of the date of publication and may be modified in the future.

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:

Reporting to the Senior Director, Statistical Programming, the Associate Director, Statistical Programming will be responsible for implementing statistical analyses using SAS and performing quality review of SAS programs and deliverables for in-house analyses as well as out-sourced programming deliverables. This individual will also perform programming analyses to generate ad-hoc requests for publications and presentations.

This is a remote position that will work closely with Biostatistics, Data Management, Clinical Operations, Regulatory, Global Pharmacovigilance, and other related disciplines, as well as CROs.

Responsibilities:

• Function as lead programmer to produce and/or validate tables, listings, figures, and analysis datasets in response to regulatory requests, publication requests, and ad-hoc analyses; write specifications to describe programming needs.
• Develop/review TFL shells, SDTM and ADaM specifications in collaboration with biostatisticians and other clinical development colleagues.
• Work closely with Data Management and Biostatistics to ensure final databases, analyses, and reports are accurate.
• Partner with or oversee CROs or Programming vendors to perform the tasks described above.
• Ensure the proper collection, management, and documentation of clinical trial data according to regulatory requirements.
• Manages project timelines and schedules of specific phases of projects and collaborates with internal personnel and outside customer representatives.
• Identify problems and develop global tools that increase the efficiency and capacity of the Statistical Programming group (e.g., macros or graphical user interface applications).

Competencies Include:

•  Adaptability/Flexibility – The ability to adapt to working effectively within a variety of situations; adapts enthusiastically to organizational change and to changes in job demands.
• Communication and Teamwork – Ability to effectively express ideas in written and oral context; to work co-operatively with others; genuine desire to be a part of a team and contribute to organizational and team goals.
• Problem Solving – Ability to understand a situation or problem by breaking it down into smaller pieces using a systematic approach and to identify patterns and connections between situations that are not obviously related.
• Relationship Building – Builds productive working relationships and effectively communicates across a diverse spectrum of people.
• Organizational and results orientation – Ability to plan and handle multiple responsibilities simultaneously and still meet high quality and timeliness standards under pressure.

 Qualifications:

• Master’s Degree in statistics, mathematics, computer science, or related scientific/medical field.
• 8+ years of (SAS) statistical programming experience in a clinical trial setting (industry/CRO).
• Advanced SAS programming skills - procedures and options commonly used in clinical trials. reporting, including Macro language, BASE SAS, SAS/STAT, and SAS/GRAPH, validation/QC, experience generating listings, tables, figures.
• Hands-on knowledge of CDISC SDTM and ADaM models and transforming raw data into these standards.
• In-depth understanding of CDISC standards including SDTM and ADaM models and extensive experience of their implementation in clinical trials.
• Familiar with regulatory guidelines (FDA, EMA, ICH) related to clinical trials, statistics and data handling in clinical development setting, and advanced knowledge of submission requirements and standards.
• Experience with outsourcing programming activities and overseeing services provided by CROs and contractors.
• Advanced understanding of statistical concepts in support of clinical data analysis.
• Advanced knowledge of programming standards and processes.
• Oncology experience is required.
• Skilled at performing quality control checks of SAS code and outputs produced by other Statistical Programmers.

What You Will Contribute To Altos

As a Senior Project Manager at Altos, you will act as an operational anchor with a big-picture mindset for the Institute of Computation (IoC). Leveraging your own background in science, you will bridge the gap between complex biological questions and rigorous operational execution using project management. You will not just track tasks; you will actively shape how cross-functional teams of biologists, data scientists, and machine learning scientists and engineers collaborate to achieve ambitious goals. This role is designed for an operational expert who excels at translating abstract scientific goals into actionable project plans, connecting the dots between daily tasks and broader program objectives, and ensuring alignment across computational, scientific, and business units.

Responsibilities:

• Plan & Execute: Translate high-level scientific intent into actionable project plans for 4-6 multidisciplinary projects. Maintain and track visibility on goals, milestones, dependencies, and timelines to ensure delivery within scope and budget.
• Operational Execution & Big Picture Alignment: Collaborate closely with scientific leads to translate their vision into reality. You will ensure the team understands how their daily tasks contribute to the broader mission, proactively identify risks, and drive the accountability needed to ensure research milestones are met on time and within scope.
• Operational Coordination: Coordinate team operations, including meeting cadence, agendas, and workflows. Ensure meetings are effective, focused, and result in clear action items.
• Documentation & Knowledge Management: Own the "single source of truth" for projects. Document meeting notes, key decisions, and lessons learned, ensuring they are accessible to all stakeholders.
• Cross-Functional Communication: Serve as the bridge between diverse disciplines to ensure seamless handoffs between scientific, computational, and business units.
• Process Improvement: Design and implement pragmatic workflows that improve operational efficiency without creating unnecessary bureaucracy.

Who You Are

Minimum Qualifications:

• Education: BS or MS in life sciences, computational biology, business, or a related field.
• Experience: 
• 5+ years of project management experience within biotechnology, computational biology, AI/ML, or pharmaceuticals. 
• Experience managing large-scale data generation (omics, imaging) and machine learning model development is highly preferred. 
• You started your career 'at the bench' (wet lab or computational) and made a deliberate pivot into professional Project Management.
• PMP, PRINCE2, or Agile certifications are a plus, but real-world experience managing complex R&D portfolios is prioritized.
• Deep Project Management Toolbox: You are an expert in a range of project management methodologies (Agile, Waterfall, Kanban, Hybrid) and know exactly when to deploy which tool. You don't force "process for process's sake"; you pragmatically select the right framework to fit the ambiguity of early-stage discovery.
• Strategic & Tactical: You function at dual altitudes - comfortable understanding the broader roadmap one hour, and deep-diving into Jira tickets, meeting minutes, or resource allocation the next.
• Communicator & Influencer: You can translate complex technical goals for diverse audiences and have the confidence to influence stakeholders without formal authority.
• Operational Mindset: You are an analytical problem-solver who is results-driven, detail-oriented, and able to work autonomously with minimal supervision.
• Tool Proficiency: High proficiency in project management platforms (e.g., Jira, Smartsheet) and Google Suite.

The hourly range for remote in the UK only:

• Hourly rate range: £29.00 - £36.00

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

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Thank you for your interest in Altos Labs! Please drop your resume here if you did not discover a job you are interested in applying for. Your profile will be added to our system and we will consider you for future job opportunities if we think you are a good fit for a position. 

In the meantime, be sure to regularly check our job board -- we're posting new jobs every week.

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.