Postdoctoral Researcher in Computational Biology in Oxford

We have an exciting opportunity for a highly motivated Postdoctoral Research Scientist in Computational Biology to join the Oxford Vaccine Group (OVG) as part of the Correlates of Immunity - Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven analytics to accelerate vaccine discovery.

The postholder will contribute to the systems vaccinology and systems biology workstream of the programme, performing the analysis and integration of high-dimensional immunological and clinical datasets generated from vaccination, natural infection, and controlled human infection studies. The Postdoctoral Research Scientist in Computational Biology will apply established and emerging bioinformatics, statistical modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics.

Working closely with senior computational biologists, immunologists, clinicians, and experimental scientists, you will support study design, data interpretation, and reporting, and contribute to the development of robust, reproducible computational pipelines suitable for downstream integrative and AI-driven discovery. The role includes training PhD students, contributing to grant applications, project planning, and leading the preparation of high-quality publications and presentations within a highly collaborative, multidisciplinary research environment.

You will be working in a growing department within the Medical Sciences Division. The Department of Paediatrics is a world leader in child health research and hosts internationally renowned research programmes in drug development, gastroenterology, haematology, HIV, immunology, neuroimaging, neuromuscular diseases and vaccinology. The Oxford Vaccine Group is a world-leading academic research group conducting clinical and translational studies to advance vaccine development working with a diverse portfolio funded by industry, government and charitable organisations.

This position is offered full-time on a fixed-term contract initially for two years with the possibility to extend provided further external funding is available.

About the department: The Department of Paediatrics has been honoured with the Athena Swan Gold award, a national gender equality charter, recognising the Department's innovative policies and practices. We are committed to the professional development of our staff by providing up to ten paid days annually for skill enhancement and allowing applications for additional training funding. By joining us, you will have the opportunity to contribute to a forward-thinking department. We welcome new staff with ideas who are willing to shape the future of the department that thinks about its staff and wellbeing.

In addition to the University of Oxford wellbeing resources, the Department of Paediatrics sponsors weekly exercise classes such as yoga and bootcamp sessions as well as a choir. For staff on work visas, we also offer financial assistance towards visa renewal fees. These activities are designed to promote physical and mental wellbeing among staff members.

You will hold a PhD/DPhil (or be near completion) in Bioinformatics, Statistics, Mathematics, Computational Biology, or a closely related discipline, with sufficient specialist knowledge to contribute effectively to an established systems vaccinology or systems biology research programme. You will have demonstrable experience in the analysis of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single-cell sequencing, gene expression, proteomics, or metabolomics.

You will be able to manage your own research activities, deliver robust and reproducible bioinformatics analyses to deadlines, and communicate results clearly through written reports, publications, and presentations. You will have a collaborative approach, with the flexibility to work effectively across multidisciplinary teams spanning experimental biology, clinical research, and computational science.