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Researcher in Agentic AI for Mechanistic Cancer Discovery

On-site in Oxford·Added 4 days ago (last checked 8 Oct)

Overview

Job details

  • Apply by Tuesday 27 October

    The date the employer’s listing closes.

Requirements

  • Work on-site in Oxford

    No relocation package mentioned.

Skills

The role

Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and treatment of disease.

We are seeking a Researcher to join Trey Ideker's multidisciplinary research team at the Big Data Institute (BDI). You will contribute to a strategic research programme aimed at developing agentic artificial intelligence for biomedical discovery and genotype-to-phenotype modelling. You will formulate mechanistic biological hypotheses and analyse data from genetic, genomic, clinical, and functional evidence, design and implement multi-agent systems for scientific reasoning and develop agents capable of interrogating scientific literature, biomedical databases, genomic and multi-omics datasets.

Applicants should hold, or be close to completing, a PhD/DPhil in bioinformatics, computational biology, systems biology, cancer biology, functional genomics, or another relevant discipline. You will have experience conducting hypothesis-driven biological research, a strong understanding of how causal and mechanistic knowledge is established in biology and demonstrated expertise in applying computational methods to biological discovery using genomic, functional-genomic, multi-omics, or other high-dimensional biomedical data.

This post is full time (part time considered) and fixed term post for 3 years.

The closing date for applications is noon on 27 October 2026.

You will be required to upload a CV and a cover letter as part of your online application. The cover letter should clearly describe how you meet each of the selection criteria listed in the job description.

Location

University of Oxford · OX3 7LF

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