Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Old Road Campus, Headington, Oxford, OX3 7LF
We are seeking a postdoctoral researcher with a strong background in epidemiology, biostatistics or a related field to contribute to the ATLAS Cancer Grand Challenges programme and the Unit's broader portfolio of research investigating cancer risk and prevention. This is an exciting opportunity for the appointee to work closely with Professor Ruth Travis, Dr Karl Smith-Byrne and other members of the research team, using large-scale epidemiological and molecular data from prospective cohort studies.
The main responsibilities will include managing and analysing complex epidemiological and molecular datasets, including high-dimensional omics data such as multiplex proteomics. The postholder will contribute to the planning and delivery of ATLAS studies, prepare and clean large-scale datasets, apply appropriate statistical methods, and assist in developing reproducible analytical pipelines. Additional duties will include contributing to study design and interpretation, preparing scientific reports and publications, presenting findings at academic meetings and conferences, and supporting wider academic activities within the Department, including teaching, mentoring and supervision where appropriate.
You will hold, or be close to completing, a PhD/DPhil in epidemiology, biostatistics or a related field, and have experience analysing health-related or epidemiological data and managing complex projects involving molecular data. You will have experience using statistical software such as R, Stata or Python, together with the ability to manage and analyse complex datasets and contribute to scientific publications and presentations. You will also have excellent communication and organisational skills, strong attention to detail, and the ability to work both independently and collaboratively. Experience with large cohort datasets, international collaborations, and the analysis of omics or proteomic data would be advantageous.
In return we offer an excellent benefits package including:
This role is based in Oxford, and offered on a full-time basis (part-time considered). It is a fixed-term post for 2 years.
The closing date for applications is noon on 10 September 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.
Tagged as: Life Sciences
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