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 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 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 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. A strong publication record and evidence of independent problem-solving are essential. Also, exceptional communication, networking and teamwork skills. Candidates who have submitted their PhD thesis but are awaiting award are encouraged to apply. Please review the Further Particulars for the full Personal Specification.

The Department of Radiology offers an outstanding environment for research and training, with direct access to state-of-the-art facilities, high-performance computing, and a vibrant imaging research community.

If you have a passion for advanced imaging research, data sharing, and collaborative science, we would love to hear from you.

The closing date for applications is 01/02/2026

The funds for this post are available for 1 year in the first instance.

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.

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.

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