Senior Researcher in Functional Genomics

Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Old Road Campus, Headington, Oxford, OX3 7LF We are seeking a Senior Researcher to join a joint research programme between the Big Data Institute (BDI) in the Nuffield Department of Population Health and the Centre for Human Genetics in the Nuffield Department of Medicine at the University of Oxford, under the supervision of the BDI Director. The programme aims to leverage large-scale biomedical resources, including UK Biobank, to develop interpretable, biologically grounded AI systems to understand the genetic origins of disease, with a particular focus on cancer. The successful candidate will play a leading role in developing high-throughput and highly automated workflows to investigate the functional impact of germline and somatic mutations in cells and tissues. A central goal of the role is to design experimental and computational pipelines that enable the validation of hypotheses generated by upstream AI models, particularly those relating to genotype-specific vulnerabilities in cancer cells. The work therefore requires expertise spanning functional genomics, bioinformatics, and machine learning to support the generation, interpretation, and screening of large-scale experimental and computational outputs. The successful candidate will contribute intellectual leadership to the research programme, leading collaborative projects and helping shape its strategic direction across both departments. The role will involve developing innovative experimental pipelines, publishing high-impact research, contributing to grant development and external funding applications, and mentoring junior researchers.

Applicants should hold a PhD/DPhil in cell biology, cancer biology, or a related discipline, with significant postdoctoral research experience. The ideal candidate will have expertise in functional genomics and/or proteomics, strong quantitative and bioinformatics skills, and experience working with high-throughput genetic screening approaches, such as prime editing or related technologies. A strong publication record, experience contributing to grant applications, and excellent communication and collaboration skills are essential.