Principal Scientist, Oncology Data Science (Translational Science) Full Time on the ground NEW

Business Introduction: At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting‑edge technology to transform people’s lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients’ needs and have the highest probability of success. We’re uniting science, technology, and talent to get ahead of disease together.

For candidates seeking to be located at our Stevenage site, this role will temporarily be based at Stevenage. However, the Company plans to relocate its offices to Cambridge, UK. The location of this role will therefore subsequently change to Cambridge, UK in accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029.

Position Summary: The GSK Oncology Data Science team in R&D Translational Science is seeking a Translational AI scientist to build ML applications for a long‑sought‑after problem: if we alter a patient tumor’s molecular state in silico, can we predict how their clinical trajectory will change? To tackle this problem, you will integrate and validate multimodal foundation models; bridge functional genomics, spatial omics, and real‑world data; and apply cutting‑edge causal inference techniques. We operate with high velocity at the intersection of machine learning, causal inference, functional genomics, spatial biology, and real‑world clinical data; your expertise, execution, technical leadership and communication will drive our efforts to bring the right therapies to the right patients.

Responsibilities

• Own the pipeline and develop advanced ML architectures to integrate complex multimodal datasets, including single‑cell, spatial omics, histopathology, functional genomics, and real‑world clinical data.
• Partner closely with wet‑lab scientists, clinicians, and pathologists to validate machine learning models, including in‑silico perturbations within the tumor microenvironment against ground‑truth data (counterfactual validation).
• Develop approaches to extract interpretable features from models to generate testable oncological hypotheses and link insights to clinical pipeline decisions such as asset prioritization and patient subpopulation selection.
• Contribute clean, reproducible tooling to cross‑team frameworks. We enforce good engineering practices in our research—utilizing code architecture planning, clean code and automated testing to build trustworthy, reusable code.
• Maintain cutting edge knowledge of advancements, share with the team and maintain our team as a thought leader through publications in high‑impact venues and engaging with the broader community.

Why You?

Basic Qualification

• PhD (or equivalent experience) in a quantitative field (Applied ML, Computer Science, Physics, Systems/Computational Biology, or equivalent) with 1+ years of industry or productive post‑doctoral academic experience.
• Experience with deeply embedded in cancer / computational biology, with a strong understanding of tumor microenvironment dynamics and high dimensional datasets.
• Experience with analytical and modelling skills, including expertise in statistical and machine learning approaches.
• Experience with the analysis of single cell omics data.
• Experience in one or more of the following: statistical modelling of functional genomics screening datasets (e.g., bulk CRISPR screens, Perturb‑seq) or spatial omics.
• Experience with Python and deep learning frameworks (PyTorch) for data processing and machine learning model development, with a strong grasp of software engineering fundamentals (e.g., version control, modular design, CI/CD).

Preferred Qualification

• Experience with multi‑modal integration, including spatial transcriptomics/proteomics, histopathology, and single cell omics data.
• Experience working with longitudinal clinical health record trajectory data.
• Familiarity with R for specialized statistical modelling.
• Experience with causal inference and individual treatment effect modelling.
• Experience with AI agent‑driven workflows and coding tools.
• Experience with generative deep learning approaches, including flow matching, diffusion and causal transformer models.
• Excellent written and oral communication skills, with a proven ability to present complex computational concepts to technical and non‑technical stakeholders.

Work model: This role is hybrid. You will balance on‑site collaboration with focused remote work.

Skills: Applied Statistics, Data Analysis, Data Engineering, Data Science, Datasets, Drug Development, Drug Discovery Process, Drug Target Identification, Genetic Analysis, Genomic Analysis, Machine Learning (ML), Software Engineering.

If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $121,275 to $202,125. The US salary ranges take into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long‑term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.

Germany Salary Range / Gehaltsbandbreiten Deutschland: EUR 74,250 to EUR 123,750. For positions covered by collective bargaining, employment conditions and remuneration are determined by the applicable collective agreements for the chemical industry as well as internal policies. More detailed information on compensation will be provided during the recruitment process. Depending on the role and internal policies, the position may also be eligible for a bonus (if applicable and based on defined, non‑discretionary criteria) and/or awards for exceptional performance (granted at the employer’s discretion). All benefits arising from the applicable collective bargaining agreement, such as holiday allowance and additional paid time off, will be provided in full, in accordance with that agreement and German law. Other benefits may also be offered, which may include health & wellbeing benefits, pension plan and paid parental leave & care of family member leave.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

If you require an accommodation or other assistance to apply for a job at GSK, please contact the appropriate Recruitment Staff by emailing us at usrecruitment.adjustments@gsk.com.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements.

For more information, visit https://openpaymentsdata.cms.gov/.

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