Principal Scientist Full-time NEW

Principal Scientist, Oncology Data Science

We create a place where people can grow, be their best, be safe, and feel welcome, valued and included. We offer a competitive salary, an annual bonus based on company performance, healthcare and wellbeing programmes, pension plan membership, and shares and savings programme.

We embrace modern work practices; our Performance with Choice programme offers a hybrid working model, empowering you to find the optimal balance between remote and in-office work.

The GSK Oncology team is seeking a highly motivated computational biologist to play a pivotal role in shifting our understanding of cancer. While many models in oncology focus solely on predicting outcomes, we are dedicated to developing new approaches that understand disease not as static labels or endpoints, but as dynamic, evolving biological states.

By integrating (bulk, single cell and spatial) multi-omics and clinical data, you will characterize disease heterogeneity, model how disease changes over time and under treatment, and investigate how biological context influences treatment response and resistance. This work focuses on understanding, and ultimately shaping, disease trajectories in a biologically meaningful way, directly supporting GSK's ambitious goal to deliver transformative oncology therapeutics to patients. You will work at the interface of data, biology, and experimentation, tackling real questions in close collaboration with experimental and clinical teams, with the goal of making data-driven approaches more interpretable, robust, and actionable.

In this role you will:

• Analyze and integrate complex multi-omics and clinical data to characterize disease heterogeneity and drive decision-making insights.
• Develop and apply advanced models that capture disease states and their evolution, to predict and influence disease trajectories.
• Investigate how biological context and underlying mechanisms influence treatment response and resistance.
• Collaborate closely with experimental scientists to generate and test mechanistic hypotheses, translating complex data into actionable insights for drug discovery.
• Contribute to the development of frameworks and computational tools that support better therapeutic decision-making and advance our oncology portfolio.
• Communicate complex scientific findings clearly to both technical and non-technical audiences, acting as a subject matter expert within interdisciplinary teams.
• Maintain current knowledge of advancements in cancer research, computational biology, and AI/ML methods.

Basic Qualifications & Skills:

• PhD (or equivalent experience) with postdoc/industry experience in Computational Biology, Bioinformatics, Systems Biology, or a related field.
• Strong understanding of biological mechanisms and disease processes, particularly within oncology.
• Proven experience working with high-dimensional biological data.
• Strong analytical and modeling skills, including expertise in statistical or machine learning approaches.
• Experience in systems biology and/or network analysis.
• Ability to work effectively in interdisciplinary and collaborative teams.
• Proficiency in programming languages such as Python or R for data analysis and model development.

Preferred Qualifications & Skills:

• Experience with spatial transcriptomics and/or proteomics analysis
• Experience with multi-omics integration or trajectory inference methods.
• Familiarity with advanced machine learning methods, including deep learning.
• Experience working with perturbation or longitudinal data.
• Highly independent, eager to learn new areas, and build expertise, with a sense of accountability.
• Excellent written and oral communication skills, with the ability to present complex data to varied audiences.

Closing Date for Applications – (COB) 29/05/2026

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Please take a copy of the Job Description, as this will not be available post closure of the advert. When applying for this role, please use the 'cover letter' of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.

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.

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.

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.

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