AI​/ML Engineer, Oncology AI

Job Location

Site Name:
Cambridge 300 Technology Square, London The Stanley Building, South San Francisco 611 Gateway Blvd

Mar 5 2026

At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI.

The opportunities for machine learning extend to many other areas of our business, including medicine safety, manufacturing, and supply chain. To realize these opportunities, GSK has created a global Artificial Intelligence and Machine learning group (AI/ML), with locations in London, San Francisco, Boston, Philadelphia, and Heidelberg, to focus on the development and application of machine learning to problems of critical importance  possess a world‑leading data and computational environment (including specialist hardware) to enable large‑scale, scientific experiments that exploit GSK’s unique access to data.

By actively engaging with the machine learning community and publishing our research, code and models built on public data, the AI/ML group operates at the cutting‑edge of machine learning research. To help us, we seek a passionate researcher who wishes to turn their talents to the application of causal machine learning to the healthcare sector. You will be working with multiple Research Engineers on building products to support multiple large‑scale projects within AI/ML.

In addition, the researcher will learn about the pharmaceutical industry and software engineering and translate their research into tools that aid discovery and development of transformational medicines and vaccines. You will have access to outstanding experts in biology, clinical and translational research, chemistry, (software) engineering, data science and machine learning; unrivalled data sources and GSK’s state‑of‑the‑art laboratory and compute infrastructure to help you develop and validate your machine learning research.

• Design and implement novel scientific approaches for biophysical modeling and foundation model‑driven analysis of multi‑modal clinical and genomic data for biomarker and target discovery to improve patient selection and enable next‑generation assets.
• Design, develop, and implement analytical solutions using a variety of commercial and open‑source tools (common tools include PyTorch and scikit‑learn).
• Connect and collaborate with subject matter experts in biology, genomics, and medicine.
• Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models.
• Develop and embed automated and agentic processes for predictive model validation, deployment, and implementation.
• Deploy your algorithms to production to identify actionable insights from large databases.

We are looking for professionals with these required skills to achieve our goals:

• Master’s degree in computer science, applied math, statistics, physics, systems biology, computational biology, bioinformatics, or related field
• Experience in Python programming and knowledge in machine learning, statistics, and applied math.
• Familiarity with modern machine learning methods (generative models, representation learning)
• Experience in building deep learning models, preferably with exposure to biophysical modeling, functional genomics, molecular and cellular biology or to modeling dynamical systems
• Experience with at least one Deep Learning framework such as Py Torch

• PhD in computer science, applied mathematics, statistics, physics, systems biology, computational biology, bioinformatics, or a related field.
• Experience in analyzing real‑world and/or clinical data.
• Experience in incorporating agentic models into ML workflows
• Understanding of best practices in software engineering, including training and operating algorithms at…