Computational Biologics Design – Associate Principal Scientist

AstraZeneca plc; Cambridge; Hybrid; GBP 120,000 - 150,000; Full time

Job summary

AstraZeneca plc in Cambridge is seeking an Associate Principal Scientist to lead in silico design for biologics, integrating AI and structural biology to shape oncology, respiratory and cardiovascular programs. You will build scalable analytics, drive new capabilities, and mentor colleagues while collaborating with discovery and data science teams to accelerate development.

The role emphasizes end-to-end data integration, cross-functional leadership, and delivery of actionable insights that

Qualifications

• PhD in a relevant field (e.g. Structural Biology, Computer Science, Bioinformatics, Physics or Mathematics)
• Experience applying data analysis methods in computational structural biology
• Experience with structural modelling platforms (Schrödinger, Rosetta)
• Familiarity with antibody discovery and optimisation, protein structures
• Proven ability to apply generative AI, ML or DL to design and optimise proteins, VHHs and antibodies
• Strong communication and attention to detail; able to collaborate with diverse teams
• Experience working within a team environment
• Act with integrity and do the right thing

Responsibilities

• Own the computational strategy for multiple therapeutic programs and influence design decisions
• Co-develop scalable structural analytics workflows with discovery and data science teams
• Contribute to end-to-end data capability linking structural, sequence and experimental data to actionable insights
• Lead evaluation and deployment of next-gen computational tools and platforms
• Drive AI-driven design to optimise proteins, VHHs and antibodies for developability
• Collaborate with external partners on strategic projects
• Communicate complex concepts clearly and mentor colleagues to raise best practices
• Deliver progress for current programs and build reusable frameworks across modalities

Skills

Computational biology

Structural modelling

Generative AI in biology

Machine learning

Team collaboration

Scientific communication

Attention to detail

Cross-functional work

Education

PhD in Structural Biology/Computational Biology

Tools

Schrödinger

Rosetta

Job description

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.

We welcome your application not later than 11th October 2026

Date Posted 01-Oct-2026

Closing Date 11-Oct-2026

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.