About the role
About Relation Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. The opportunity Relation is offering an outstanding opportunity for a Data Scientist to support computational drug discovery and drug-ability efforts focused on antibodies. You will work closely with external deep learning–driven antibody design platforms to critically evaluate generated candidates, extract insights, and integrate learnings into internal discovery strategies. Day to day, you will Support computational antibody discovery and drug-ability efforts across research programmes. Work with internal and external teams to evaluate and interpret computationally generated antibody candidates. Contribute computational and structural biology expertise to multidisciplinary project teams. Help extract insights from sequence, structural, and modelling data to inform discovery decisions. Collaborate with machine learning and experimental scientists to support ongoing research activities. Contribute to the development and refinement of internal computational discovery strategies and workflows. Professionally, you will have A PhD in computational biology, structural bioinformatics, computational structural biology, or a related field; or a Master’s degree with equivalent industry experience. 0–2 years of experience in biotech, pharma, or a relevant postdoctoral environment. Experience with computational approaches for antibody design and development. Antibody sequence and repertoire analysis. Structural modelling of antibodies and antibody-antigen complexes. Computational protein engineering and affinity optimisation. Machine learning and generative modelling for antibody design. Developability and biophysical risk assessment. Knowledge of Python as a programming language. Understanding of the drug discovery process.