Postdoctoral Research Assistant in Biomedical Image Analysis

We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image analysis and is increasingly used in cancer research to uncover morphological features linked to disease pathology and severity. Similarly, molecular profiling through ‘omics technologies has provided new insights into the disrupted biological processes underlying cancer.

This project is initially funded until March 2027 and is part of a collaborative initiative supported by the Oxford Cancer Centre. The postdoctoral researcher will join the Department of Engineering Science at the Old Road Campus Research Building, with Professor Jens Rittscher as line manager. The role involves coordinating work with Simon Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work at the intersection of these research areas.

You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer research, deep learning and biomedical image analysis are essential. Strong programming skills in Python and a keen interest in cross-disciplinary research are also required.

Informal enquiries may be addressed to Jens Rittscher (email: jens.rittscher@eng.ox.ac.uk).

For more information about working at the Department, see  www.eng.ox.ac.uk/about/work-with-us/.

Only online applications received before midday on 30 June 2025 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.

The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.

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