Location: Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford, OX3 7LF
We are seeking a full-time postdoctoral research scientist to join research groups of Professor Jens Rittscher and Professor Konstantinos Kamnitsas at the Department of Engineering Science, Institute of Biomedical Engineering, Headington. The post is funded by Wellcome Trust Bioimaging Technology Development Award. The initial contract is fixed-term for 18 months, with the possibility of an extension, subject to funding.
You will apply and develop cutting-edge machine learning methods to integrate and analyse multi-omic data to identify disease phenotypes. A key aspect of the role is to bridge research and implementation. You will also develop novel algorithms using state-of-the-art computer vision and machine learning techniques (segmentation, multimodal AI, foundation models, agentic frameworks) to detect and analyse tissue architecture components and subtle disease related changes. The postdoctoral researchers will work closely with software engineers and data platform developers to translate research prototypes into practical tools, ensuring robustness, reproducibility, and usability of developed tools for wider adoption.
You should hold a relevant PhD/DPhil (or be near completion) and possess strong technical expertise in deep learning, such as models for image segmentation, classification, multi-modal processing, foundation models, or agentic frameworks. An extensive background in computer vision and/or biomedical image analysis is essential, as well as the ability to manage own academic research and associated activities.
Informal enquiries may be addressed to Jens Rittscher (jens.rittscher@eng.ox.ac.uk) and Konstantinos Kamnitsas (konstantinos.kamnitsas@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 2nd November 2026 can be considered. You will be required to upload a cover 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.
£39,424 to £47,779 per annum