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"Postdoctoral Research Associate in Mathematics for Technical Art History (Fixed Term)"

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Postdoctoral Research Associate in Mathematics for Technical Art History (Fixed Term)

University of Cambridge - Department of Applied Mathematics and Theoretical Physics

Location:Cambridge
Salary:£37,694 to £46,049
Hours:Full Time
Contract Type:Fixed-Term/Contract

Placed On: 22nd December 2025

Closes: 29th January 2026

Job Ref: LE48217

We invite applications for a Postdoctoral Research Associate position at the University of Cambridge to join the Cambridge Image Analysis group in the Department of Applied Mathematics and Theoretical Physics. The successful candidate will work on the research project MakingAI: AI-Driven Integration of 'Messy' Data in Technical Art History, a close interdisciplinary collaboration between the Department of Applied Mathematics and Theoretical Physics, the Fitzwilliam Museum and the McDonald Institute for Archaeology.

The MakingAI project brings together mathematics, artificial intelligence and technical art history to develop mathematically grounded and explainable AI methods for the integration and interpretation of multi-modal, heterogeneous, incomplete and uncertain data arising in the scientific investigation of artworks and historical objects. The project aims to advance the mathematical foundations of imaging and machine learning while directly supporting research in art history, conservation and heritage science.

The postholder will be based in the Department of Applied Mathematics and Theoretical Physics within the Cambridge Image Analysis group, a research team working on mathematical imaging, inverse problems and the foundations of deep learning. The role offers a highly interdisciplinary research environment, with close interaction with museum scientists, conservators and art historians at the Fitzwilliam Museum and the McDonald Institute, as well as opportunities to engage more broadly with researchers across the University of Cambridge and international partners.

The successful applicant will contribute to the development of novel mathematical and computational methods for image analysis and AI, with a particular emphasis on interpretable and uncertainty-aware approaches motivated by real-world cultural heritage data. They will be expected to produce research of the highest academic quality, to publish in leading venues, and to participate actively in interdisciplinary collaboration, dissemination activities and, where appropriate, public engagement.

Applicants should have, or be close to completing, a PhD in Mathematics or a closely related discipline. A strong background in mathematical imaging, inverse problems and/or artificial intelligence is essential, together with excellent computational skills and the ability to develop new methodology or mathematical understanding. Prior experience in the art and cultural heritage domain is advantageous but not required; a genuine interest in interdisciplinary research and working with complex, real-world datasets is essential.

The position is funded for a fixed term of two years. The start date is flexible and can be agreed with the successful candidate. Interviews will be held as soon as possible after the closing date.

Interviews will provisionally be conducted on 17th and 18th February 2026.

To apply online for this vacancy and to view further information about the role, please click 'Apply' above.

Please submit a full curriculum vitae and provide the contact details of two academic referees (including their e-mail addresses) via the University's online application system. At least one referee should be available throughout the selection process. Informal enquiries may be addressed to Prof. Carola-Bibiane Schoenlieb at cbs31@cam.ac.uk.

Please quote reference LE48217 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.

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