Academic ConnectImaging AI Research Associate (Fixed Term)
Imaging AI Research Associate (Fixed Term)
We are excited to announce an opportunity for an Imaging AI Postdoctoral Research Associate position in the group of Marc Dewey (Professor of Radiology) in the Department of Radiology.
This position is funded by the first Academy of Medical Sciences (AMS) Professorship grant to the University of Cambridge (https://acmedsci.ac.uk/more/news/academy-international-research-professorships).
The position will play a central role in the coronary imaging AI and histology project of the AMS Professorship grant aiming to achieve the first histology-informed, near-microscopic resolution AI-based CT imaging of coronary atherosclerosis. This is a unique opportunity to help pioneer the next generation of cardiovascular imaging by combining photon-counting CT, micro-CT, 3D histopathology, and advanced AI.
During this project you will help building the first large-scale multimodal coronary CT-histology database, develop novel super-resolution algorithms, and contribute to mechanistic insights into coronary atherosclerosis development. The successful candidate will join a multidisciplinary team (www.marcdewey.de and Instagram: @dewey_team) spanning engineering, imaging, cardiovascular medicine, and computer sciences working closely with leading global partners.
You will also contribute to internationally significant randomised imaging trials led by our group, including CAD-Man and DISCHARGE, which have resulted in high-impact publications (e.g., BMJ and New England Journal of Medicine) and thereby shaped international guidelines and advanced research in cardiovascular and cardiothoracic imaging. You will also support ongoing and new multicentre imaging trials (such as INCHARGE) focused on improving the diagnosis, monitoring, and treatment of cardiovascular and cardiothoracic diseases.
- We welcome applications from technically exceptional candidates with a PhD (or equivalent) in a relevant subject area (e.g., Medicine, Computer Science, Engineering, Mathematics).
- Expertise in image data handling, multimodal registration, deep learning, strong foundation in Python, R, and SQL, and quantitative imaging are key.
- A strong developing publication record and evidence of independent problem-solving are essential.
Candidates who have submitted their PhD thesis but are awaiting award are also encouraged to apply. They will have some research experience with a developing track record of publications, and a strong foundation in software development and data analysis and ideally image analysis software and quality assurance. They will also bring excellent presentation and teaching skills and be willing to take a leading role in supervising research students.
Informal enquiries or questions relating to the application process may be directed to ClusterHR@medschl.cam.ac.uk.
The closing date for applications is: 01/02/2026
Fixed-term: The funds for this post are available for 2 years in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment.
Applicants must have (or be close to obtaining) a PhD.
Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will initially be appointed as a Research Assistant (Grade 5, Point 38 £34,610) moving to Research Associate (Grade 7) upon confirmation of your PhD award.
Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
Please quote reference RQ48442 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
Key information
Department/location
Salary
£37,694-£46,049
Reference
RQ48442
Category
Date published
6 January 2026
Closing date
1 February 2026
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