Ovarian cancer is one of the most challenging malignancies to diagnose and manage, with critical treatment decisions requiring the integration of complex, multimodal clinical evidence. Transforming this evidence into reliable, interpretable, and deployable AI is one of the most exciting open problems at the frontier of machine learning and medicine.IMPACT-OC is a new, major European multi-centre project building a multi-agent AI system for ovarian cancer, spanning imaging, genomics, histopathology, and clinical records, with privacy-preserving federated learning at its core. As a Postdoctoral Research Associate, you will join the IMPACT-OC consortium and play a leading role in the project, which brings together multimodal AI pipelines, digital twin technology, and clinician-facing deployment across eight European partner institutions.This post is a joint collaboration between the Department of Radiology and the Early Cancer Institute at the University of Cambridge. You will be co-supervised by Professor Ferdia Gallagher (Department of Radiology) and Dr Mireia Crispin-Ortuzar (Early Cancer Institute), and will be embedded across both research groups, giving you access to world-class expertise in clinical imaging and cancer AI, alongside the rich, multidisciplinary environments that each brings. You will be encouraged to take part in multiple projects, contribute ideas, shape new analytical directions and participate in publications, conference presentations and collaborative funding applications.This is a genuinely translational role, sitting at the interface of artificial intelligence, clinical oncology and radiology, and human-centred design, with real potential to shape how AI enters clinical practice. This is an opportunity for an ambitious, passionate researcher to shape methods which have the potential to make management-altering changes to the way patients are treated in the future.Fixed-term: The funds for this post are available for 2 years in the first instance.This appointment requires a Research Passport application.Informal enquiries are welcomed and should be directed to Dr Mireia Crispin-Ortuzar (mc973@cam.ac.uk) and Professor Ferdia Gallagher (fag1000@cam.ac.uk).Closing Date: 29th November 2026Interview Date: 15th December 2026 (subject to change)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 £35,302) 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, why you are applying for this role and your vision for the role (maximum 2 pages) and also include a list of publications. 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 RD51541 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.Apply online #J-18808-Ljbffr
Postdoctoral Research Associate in Agentic AI for Cancer Care (Fixed Term) in Cambridge employer: University of Cambridge
The University of Cambridge offers a dynamic and collaborative work environment, particularly within the Department of Oncology, where you will play a pivotal role in advancing cancer research. With a strong emphasis on employee growth, you will have access to professional development opportunities and the chance to work alongside leading experts in the field. The university's commitment to innovation and excellence ensures that your contributions will have a meaningful impact on clinical care and research outcomes.
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How to prepare for a job interview at University of Cambridge
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