We are seeking a full-time Postdoctoral Researcher in Computer Vision CT image analysis to join the Nuffield Department of Surgical Sciences, working in close collaboration with the Biomedical Image Analysis group. The post is funded by UK Research Innovation.

 

You will be based in Nuffield Department of Surgical Sciences, John Radcliffe Hospital as your normal place of work; but you may be able to agree a pattern of regular remote working with your line manager.

 

This is a unique opportunity to develop your career in the intersection of: Healthcare, Academia and Industry. Your research will translate to real world impact that improves patient journeys, healthcare system efficiency and environmental sustainability.

 

Your scientific research will focus on the development of machine/deep learning-based medical image analysis methods for computerised tomography scans (CT scans). Key applications of such ML/DL methods are illustrated by our prior research (PMIDs 33913675, 33234786, 33630463, 35286501) where we showed the potential for such applications to be ‘platform technologies’. We will next iteratively refine the clinical applications in different anatomical regions and in different pathological contexts. A key focus will be further refining the method of aortic aneurysm growth prediction using CT scan derived biomarkers. You are strongly encouraged to read these prior publications prior to the panel interview.

 

In addition to further excelling your skills in Computer Vision/Big Data/Machine Learning analyses, this opportunity enables you to:

 -  Work closely with clinicians and academic researchers in multiple countries across different continents.

 -  Interact with industry collaborators in different sectors of healthcare AI and gain interdisciplinary insights.

 -  Develop leadership / management skills through:

 -  Enriched support for research grant applications, including research fellowships

 -  Lead research projects through its full life cycle, including IP capture and downstream exploitation.

 

You will have access to an unprecedented CT image repository (in terms of its volume and diversity) managed by the AICT consortium, as well as datasets acquired through open access platforms and image providers. In addition to refining the existing DL architecture, we will explore the utility of Foundation Models (diffusion models, active learning) and other emerging DL paradigms to this foundation data source.

 

You should possess a relevant PhD/DPhil (or be near completion), as well as relevant experience in the area.  You should also have previous experience of contributing to publications/presentations and the ability and enthusiasm to deliver results in interdisciplinary research.  Excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings are also essential.  Experience in the analysis of CT images, particularly in the context of translational projects would be beneficial.

 

This role is also sponsorable for a Global Talent or Skilled Worker Visa.

 

This full-time post is available immediately and is fixed-term to 17 October 2025 in the first instance, with a possible extension subject to funding.

 

Informal enquiries may be addressed to Prof Regent Lee (regent.lee@nds.ox.ac.uk) or Prof Vicente Grau (vicente.grau@eng.ox.ac.uk).

 

For more information about working at the Department, see https://www.nds.ox.ac.uk/

 

You will be required to upload a covering letter, 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. Please quote reference NDSA908 on all correspondence.

 

Only online applications received before 9th Nov 2023 can be considered. Short listing status will be notified by 17th November. Interview (Teams) will be held on the afternoon of 24th Nov 2023.