Job Title: Computational Biologics Design – Associate Principal Scientist

Location: Cambridge

Salary: Competitive

Introduction to role:

Are you ready to harness AI and computational structural biology to shape the next generation of biologics that change patient outcomes? In this role, you will lead in silico design for biologic therapeutics across oncology, respiratory and cardiovascular disease areas, turning complex structural and experimental data into decisive insights that advance our pipeline.

You will join a growing, highly collaborative group focused on data-driven biologics design. Working side by side with discovery and data scientists, you will build robust structural analytics workflows, integrate new computational capabilities and help set the standard for how we design, optimise and select antibodies, VHHs and other protein modalities. Where will you take the science next?

Accountabilities:

In Silico Project Leadership: Own the computational strategy for multiple therapeutic programs, partnering with project leads to inform design hypotheses, prioritise constructs and influence key decisions.

Structural Analytics Workflows: Co-develop scalable, reproducible structural analytics workflows with discovery and data science colleagues, accelerating candidate design and optimisation.

End-to-End Data Capability: Contribute to an integrated, end-to-end data analysis capability that connects structural, sequence and experimental data to actionable recommendations for project teams.

New Computational Capabilities: Lead the evaluation, integration and deployment of next-generation computational tools and platforms to enhance biologics discovery and design.

AI-Driven Design and Optimisation: Drive innovative structural, generative and machine learning methods to design and optimise proteins, VHHs and antibodies for potency, specificity and developability.

External Collaborations: Participate in and shape strategic collaborations with external partners, translating emerging science into practical tools and impact for our programs.

Scientific Communication and Influence: Communicate complex concepts clearly to non-experts, present at internal and external meetings and mentor colleagues to elevate computational best practices.

Impact Progression: Deliver immediate modelling and analytics that move current programs forward; over time, establish reusable frameworks and capabilities that uplift multiple modalities and therapy areas.

Essential Skills/Experience:

• PhD in relevant field (e.g. Structural Biology, Computer Science, Bioinformatics, Physics and Mathematics)
• Knowledge of computational structural biology and demonstrated application of data analysis methods
• Experience with structural modelling platforms (e.g. Schrodinger, Rosetta etc)
• Familiarity with antibody discovery & optimisation, protein structures
• Skilled in applying generative AI, Machine learning or deep learning to design and optimise proteins, VHH and antibodies
• Strong, professional communication skills and excellent attention to detail, capable of developing good working relationships with diverse individuals
• Experience working within a team environment
• Acts with integrity and does the right thing

Desirable Skills/Experience:

• Knowledge of FAIR data principles
• Experience with the analysis of large structural, sequence and experimental datasets.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here, your expertise fuels a bold mission to push scientific frontiers and transform outcomes in some of the toughest diseases, including cancer. You will work at the intersection of cutting-edge computation and lab discovery, alongside diverse minds who combine academic rigor with real-world delivery. Our global network spans hundreds of collaborations across many countries and includes partnerships with leading oncology centres, giving you access to breakthrough ideas, high-quality data and the chance to see your methods scale from concept to clinic. We bring surprising combinations of experts together to spark fresh thinking, value kindness alongside ambition and equip you with the technology, mentorship and remit to make a meaningful, patient-focused impact.

Call to Action:

Step into this role to shape breakthrough biologics with real-world impact—share your CV to start the conversation today!

We welcome your application not later than 11th October 2026

Date Posted

Closing Date