Postdoctoral Research Assistant in Biomedical Image Analysis

Department of Engineering Science, Institute of Biomedical Engineering, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, Oxford, OX3 7LF

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.

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.

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