Associate Director Predictive Agentic Target Biology in Stevenage

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.

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.

You will lead predictive and agentic target biology work to improve how we find and prioritise targets for new medicines. You will combine computational and experimental approaches to predict target biology, safety, and translational potential. You will work closely with biologists, data scientists, engineers and project teams to influence project decisions. We value clear communicators who build robust, reproducible methods and focus on practical impact for patients. This role offers visible project influence, career growth, and the chance to unite science, technology and talent to get ahead of disease together. This role will provide you the opportunity to lead key activities to progress your career.

These responsibilities include some of the following:

• Lead development and application of predictive models and agentic workflows to evaluate target tractability and safety.
• Design hypothesis-driven experiments and computational tests to validate target biology and mechanism of action.
• Integrate multimodal biological data such as genomics, transcriptomics, proteomics and functional screens.
• Translate biological questions into clear computational and experimental plans and deliver documented pipelines.
• Provide timely, evidence-based recommendations to project teams for target prioritisation and go/no-go decisions.
• Mentor colleagues and promote best practices in model validation, reproducibility and transparent reporting.

Basic Qualification:

• PhD in biology, computational biology, bioinformatics, systems biology or a related life sciences field; or MSc with substantial relevant experience.
• Practical experience developing and applying predictive models for biological targets or cellular phenotypes.
• Strong programming skills in Python or similar languages and experience with scientific libraries for data analysis.
• Hands‑on experience integrating and analysing multimodal biological datasets including RNA‑seq, proteomics or CRISPR screens.
• Proven track record working in multidisciplinary teams and translating research questions into actionable workflows.
• Right to work in the United Kingdom.

Preferred Qualification:

• Experience with agentic systems or orchestration frameworks that automate iterative design‑test‑analyse cycles.
• Familiarity with causal inference, mechanistic models, or systems biology methods for predicting biology.
• Experience deploying models and workflows to cloud or production environments such as Kubernetes, AWS or Azure.
• Knowledge of target safety assessment, translational biomarkers, or early pharmacology relevant to discovery.
• Record of scientific communication through publications, conference presentations or internal knowledge sharing.
• Experience mentoring or leading small scientific teams and influencing cross‑functional decisions.

This role is hybrid. You will combine remote work with regular in-office time in the United Kingdom to collaborate with colleagues and project teams.

We welcome applicants from all backgrounds and encourage people who may not meet every preference to apply. We look forward to learning about the impact you want to make.