Research Assistant in AI for Medical Imaging

Applications are invited for a Research Assistant to join a highly successful multidisciplinary collaboration between the groups of Dr Mireia Crispin and Dr Matt Hoare at the Early Cancer Institute, located on the Cambridge Biomedical Campus. Working at the interface of artificial intelligence, data science and cancer research, this work will develop next-generation computational methods to improve early liver cancer detection and accurately predict malignancy risk.

We wish to recruit a motivated individual to participate in a portfolio of data-driven projects aimed at modelling the radiological appearance of liver cancer for AI-based liver lesion detection and classification. In this role, you will be responsible for developing AI approaches to analyse liver imaging data from a large and unique in-house dataset of CT and MRI scans.

This 2-year position will expose you to cutting-edge AI methodologies, world-class clinical datasets, and a highly translational research environment that bridges the gap between computer science, radiology, and hepatology. You will develop robust and reproducible analytical pipelines and explore state-of-the-art approaches including deep learning, computer vision, foundation models, multimodal data integration, generative modelling and interpretable machine learning. Depending on your experience and project requirements, your work may include image registration, segmentation and object detection; longitudinal disease modelling; quantitative feature extraction; classification and risk prediction; and evaluation of models using clinically meaningful outcomes. You will work closely with researchers in artificial intelligence, cancer biology, radiology and clinical medicine. The role offers access to distinctive clinical datasets, specialist scientific and clinical expertise, and substantial GPU and high-performance computing resources. You will be encouraged to contribute ideas, shape new analytical directions and participate in publications, conference presentations and collaborative funding applications.

Applicants must have a degree in computer science, engineering, biology, physics, or a closely related field. The ideal candidate will have programming experience in Python and bash, alongside expertise in the analysis of large datasets and the development of machine learning models. The role holder must also have excellent written and verbal communication skills, evidence of effective collaboration, and the ability to independently solve problems, troubleshoot, and navigate relevant literature.

Prospective candidates are encouraged to contact Matt Hoare (mwh20@cam.ac.uk) or Mireia Crispin (mc973@cam.ac.uk) directly when considering an application to discuss the project in greater detail.

Fixed-term: This Evelyn Trust funded position is available for 24 months in the first instance.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a standard Disclosure and Barring Service check. This appointment also requires a Research Passport application.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements.

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.

Closing Date: 24th August 2026

Interview Date: Week commencing 7th September 2026

Please quote reference RD50503 on your application and in any correspondence about this vacancy.

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