Academic ConnectImaging Data Sharing Research Associate (Fixed Term)
Imaging Data Sharing Research Associate (Fixed Term)
We are excited to announce an opportunity for an AI and Data Sharing 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 advancing the GUIDE-IT data sharing project (www.guide-it.org), a global initiative led by us collaboratively with other teams globally that is bringing together clinical and data scientists to build a comprehensive platform for randomised medical imaging trials.
The aim of GUIDE-IT is to create the world's most accessible and rigorously curated imaging data resource. This work will enhance clinical imaging data sharing, generate valuable insights into clinical effectiveness, and foster the development of AI-driven and quantitative imaging analysis tools.
The position will play a key role in extending the GUIDE-IT network along three coordinates: geographically, for imaging modalities, and radiology subspecialties. The post will also support scalable pipelines for data harmonisation, metadata structuring, FAIR, federated learning, and secure cloud deployment.
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 and helping to further advance the GUIDE-IT network with leading existing and future 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. 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. Computer Science, Information Systems, AI, or Data Science).
- Expertise in data infrastructure, large-scale imaging datasets, and FAIR principles is key.
- Strong publication record and evidence of independent problem-solving are essential. Exceptional communication, networking and teamwork skills are required.
- They will have some research experience - with a developing track record of publications, and a strong foundation in data sharing.
- They will also bring excellent presentation and teaching skills, and be willing to take a leading role in supervising research students.
Candidates who have submitted their PhD thesis but are awaiting award are also encouraged to apply.
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 1 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 detailing your background and vision for the position, your CV, and a research publication list in the upload section of the online application. 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 RQ48440 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
RQ48440
Category
Date published
6 January 2026
Closing date
1 February 2026
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