Senior Scientist - Computational Protein Design/Bioinformatics

For over 25 years, Abcam has been providing tools the scientific community needs to enable faster breakthroughs in critical areas like cancer, neurological disorders, infectious diseases, and metabolic disorders. At Abcam, our mission is to empower scientists globally, and we aim to be the most influential life sciences company in the world.

We are seeking a Senior Scientist - Computational Protein Design and Bioinformatics to join the newly established Danaher Affinity Reagent Autonomous Laboratory hosted at Abcam in Cambridge. You will evaluate, develop, and utilise cutting-edge computational design for miniproteins, VHHs (nanobodies), and antibodies, leveraging modern machine learning approaches including large language models (LLMs) and diffusion-based generative models. This role sits at the interface of structural biology, computational modeling, and AI-driven molecule design.

You will drive the design of novel protein binders which will then be tested in a state-of-the-art autonomous wet-lab, enabling rapid design/make/test/learn cycles at scale. This position reports to the Director of Data Applications and Analytics at Abcam and is based in Cambridge, UK.

In this role, you will have the opportunity to:

• Lead computational design of miniproteins, VHHs, and antibodies.
• Apply and integrate LLM-based and diffusion-based generative models with structure- and physics-based protein design methods.
• Collaborate closely with wet-lab teams to drive iterative design/make/test/learn cycles.
• Analyze structural, biophysical, and binding data to refine models and improve design quality.
• Contribute to strategy and communicate results to internal and external stakeholders.

The essential requirements of the job include

• Expertise in AI/ML for molecular design, such as: protein structural modelling; generative protein or antibody design; optimization of binding, developability, or stability profiles.
• Familiarity with immune repertoire sequencing, phage/yeast display, or experimental modalities used to assess and optimize biomolecule properties.
• Strong grounding in statistics, applied mathematics, and computational modelling.
• Fluency in Python, including rapid prototyping, production-quality code, and use of relevant bioinformatics and ML libraries.
• Ability to navigate and solve complex, ambiguous scientific data problems with creativity and rigor.
• 5+ years of relevant experience in computational biology, bioinformatics, or AI for molecular design.

It would be a plus if you also possess previous experience in:

• Software engineering best practices and collaboration with engineering teams.
• MLOps or model lifecycle management.
• Working with databases, data integration strategies, and data modelling.
• Working in dynamic, multidisciplinary settings.
• Learning new tools and applying them to complex biological challenges.