Postdoctoral Research Associate Full-time NEW

Postdoctoral Research Associate – Department of Statistics – 24-29 St Giles', Oxford, OX1 3LB

We are seeking to appoint a Postdoctoral Research Associate to join the Oxford Protein Informatics Group (OPIG) in the Department of Statistics at the University of Oxford. You will work on a Gates Foundation–funded project in collaboration with the Draper Lab in the Department of Paediatrics, focused on the discovery and rational optimisation of broadly neutralising antibodies against blood-stage malaria. This is an exciting opportunity to contribute to cutting-edge research at the interface of immunoinformatics, structural biology, and machine learning.

You will be part of a highly collaborative research environment working across computational and experimental disciplines, with access to world-class high-performance computing resources and close interaction with leading malaria research experts.

You will be responsible for developing and applying advanced, structure-aware machine learning methods to predict antibody specificity, cross-reactivity, and developability against blood-stage malaria antigens. This will include adapting and extending computational models to analyse antibody–antigen interactions, forecasting escape mutation sensitivity, and guiding the optimisation of lead antibody candidates. You will manage your own research activities, coordinate multiple aspects of the project to meet deadlines, and contribute to the preparation of publications, presentations, and research proposals. You will also contribute to wider project development by generating new research ideas and supporting funding applications. As part of the team, you will collaborate closely with experimental and computational researchers, contribute to group discussions, and may support students and junior researchers. There will also be opportunities to engage in teaching and academic service activities within the Department.

It is essential that you hold, or are close to completing, a PhD/DPhil in computational chemistry, structural biology, bioinformatics, statistics, machine learning, computer science, mathematics, or a closely related field. You should have strong experience in Python programming and high-performance computing, along with a solid understanding of computational biology or protein modelling. Experience developing machine learning methods for protein analysis or design is required. You should be able to manage independent research, contribute to scientific publications, and communicate effectively across interdisciplinary teams. A proactive approach, strong analytical skills, and the ability to generate new research ideas and funding opportunities are important for success in this role.

This position is offered full time on a fixed term contract for 21 months (ending no later than 31 March 2028).