PhD Studentship in AI Foundation Model for Materials

Designing materials and structures with unprecedented performance requires constitutive models that can generalise across chemistries, microstructures and loading histories. Classical approaches rely on hand-crafted modelling assumptions (e.g. specific elastic - plastic - viscoelastic laws with prescribed internal variables) that must be re-tuned or completely re-built whenever the microstructure or processing route changes, limiting transferability and slowing discovery. 

In this project, we will develop Recurrent Neural Operator++ (RNO++), a foundation model for constitutive behaviour that unifies materials-knowledge representations with operator learning. 

The project is fully funded at the UK home rate and will be hosted within the UKRI AI CDT. It is funded by the UK Atomic Energy Authority and will be based at the University of Cambridge, with an expected start date of September 2026. 

Applicants should have (or expect to obtain by the start date) at least a good 2.1 degree in an Engineering or related subject. 

To apply for this studentship, please send your CV Dr Burigede Liu (bl377@cam.ac.uk) via the above ‘Apply’ button to arrive no later than 5 December 2025.

Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately for admission through the University's Postgraduate Admissions application portal; this can be done before or after applying for this funding opportunity. The applicant portal can be accessed via: www.postgraduate.study.cam.ac.uk/courses/directory/egegpdpeg. The final deadline for PhD applications is 14 May 2026, although it is advisable to apply earlier than this. Please note that there is a £20 application fee.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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