Postdoctoral Research Assistant in Computerised Tomography Image Analysis

**Contract type: Fixed-term until 17th October 2025**



**Hours: Full-time**





**About the role**



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:





* wide range of training courses available through University of Oxford and UK Research Innovation ecosystems.


* ‘on-the-job’ training through your pivotal roles in the international consortium (www.AICT.ai). In addition to developing the scientific research, you will have the opportunity to gain management / leadership skills in aspects of the consortium operations.




- 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.





**About you**



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.





**Application Process**



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.





**Committed to equality and valuing diversity**