Senior Researcher in Bio-Machine Learning Full-time NEW

Senior Researcher in Bio-Machine Learning

Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Big Data Institute, Old Road Campus, Headington, Oxford, OX3 7LF

UNIVERSITY OF OXFORD | BIG DATA INSTITUTE

Grade 8: £50,067–£59,396 per annum, including Oxford Weighting Allowance

Oxford Population Health (the Nuffield Department of Population Health) provides an outstanding environment for interdisciplinary research addressing fundamental questions about the causes, prevention and treatment of disease.

We are seeking an exceptional Senior Researcher in Bio-Machine Learning to join Oxford HELIX (AI Health Learning and Information Xchange), an ambitious new cross-University initiative bringing together expertise in artificial intelligence, biomedical science and medicine. With a physical base at the Big Data Institute (BDI), HELIX aims to establish Oxford as an international leader in developing and applying advanced AI to understand human biology and improve human health.

The successful candidate will work at the forefront of machine learning and biomedical discovery, collaborating with researchers across Oxford to develop, adapt and apply innovative AI methods to challenging scientific problems. Potential research areas include foundation models for biomedical data; multimodal learning across genomics, imaging and health records; virtual cells and tissues; AI-guided therapeutic discovery; and agentic AI for hypothesis-driven research.

You will contribute to interdisciplinary projects, develop new methodological approaches where appropriate, work with internationally recognised investigators, and contribute to scientific publications and reusable machine-learning tools. You will benefit from the BDI's strengths in population-scale data science, access to major biomedical research resources, and opportunities for professional development and collaboration across academic and industrial research.

Applicants should hold a PhD/DPhil in machine learning, artificial intelligence, computer science, statistics, data science, computational biology or another relevant quantitative discipline. You should have substantial hands-on experience developing and applying machine-learning or deep-learning methods to complex problems; strong Python programming skills; and experience with modern ML frameworks such as PyTorch, JAX or TensorFlow. Applicants with strong methodological ML backgrounds are encouraged to apply, including those wishing to enter biomedical research for the first time.

This is a full-time, fixed-term appointment for three years (part-time arrangements considered). The closing date for applications is noon on 10th December 2026. Applicants should upload a CV and cover letter clearly describing how they meet the selection criteria in the accompanying job description.