About The Role

A growing biotechnology company in Cambridge is looking for a Scientist to apply machine learning and computational biology to antibody discovery, engineering and optimisation. You will develop and validate models using internal and external datasets, working closely with experimental scientists to turn the results into testable recommendations for therapeutic antibody and protein design.

This is a great opportunity for an early-career computational scientist to build their skills in a collaborative, multidisciplinary R&D environment.

Key Responsibilities

• Develop, train, validate and evaluate machine-learning models using internal and external biological datasets.
• Apply machine learning, statistical modelling and computational biology to antibody discovery, design, optimisation and candidate selection.
• Analyse antibody sequence, structure, binding, functional and developability data to support optimisation of affinity, specificity, stability, solubility and manufacturability.
• Collaborate with experimental scientists to define scientific questions, design validation strategies and use experimental results to refine models and design cycles.
• Contribute to computationally guided library design, lead optimisation and project decision-making.
• Keep up to date with advances in artificial intelligence, protein language models, generative design and structure prediction.
• Communicate model outputs, uncertainty, limitations and recommendations clearly to multidisciplinary project teams.
• Maintain high standards of data quality, reproducibility, documentation and scientific integrity.