PhD in Multi-Modal & Multi-Fidelity AI for Fusion Materials: Data Centric Design, Validation, and Deployment, with Digilab & FOSTER

A 3.5 year UK PhD is available in the group of Prof Sandy Knowles within the School of Metallurgy and Materials at the University of Birmingham, with a tax-free stipend of £20,780 per year.

This project is co-sponsored between digilab, FOSTER Industry PhD Scheme, and University of Birmingham, with the project being industrially co-supervised by Dr Andy Corbett and Dr Cyd Cowley from digilab.

The Materials for eXtremes (M4X) research group (https://more.bham.ac.uk/M4X/) investigates new alloys for extreme environments from fusion & fission reactors, to aerospace gas turbines and concentrated solar power. This involves the design of fundamentally new alloys by computational methods; production through arc melting, powder metallurgy or additive manufacturing; characterisation using advanced electron microscopy and x-ray diffraction techniques; mechanical testing using macro/micro-mechanical methods and failure investigation; and environmental behaviour under oxidation/corrosion and irradiation damage.

Fusion power plants demand structural materials capable of operating at >650 °C with high radiation tolerance. Traditional computational materials design workflows excel in data‑rich systems (e.g. Ni & Fe alloys) but underperform in refractory and low‑activation design spaces, where data is sparse. UoB’s Materials for eXtremes (M4X) group has pioneered alloy design, gradient‑based exploration and multimodal mapping, to rapidly generate linked property-microstructure-chemistry multi-modal datasets, to efficiently produce low‑to‑medium fidelity data streams, which can also be paired to high‑fidelity industrial data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise these new multi-modal datasets to extract new insights as to the complex interlinks to enable the deploying of decision‑grade models.

The candidate should have a 1st / 2:1 class Undergraduate or Masters degree (or equivalent) in Materials Science, Physics, or related science/engineering discipline. A background in coding, data science, microstructural characterisation and/or mechanical testing would be advantageous but is not required.

To Apply please provide:
(1) A curriculum vitae (CV), (2) A Cover Letter summarising your research interests and suitability for the position, and (3) The contact details of two Referees.
Please send to Prof Sandy Knowles - a.j.knowles@bham.ac.uk via the above 'Apply' button.
www.birmingham.ac.uk/ajknowles
https://more.bham.ac.uk/M4X

Funding notes:

A 3.5 year UK PhD is available in the group of Prof Sandy Knowles within the School of Metallurgy and Materials at the University of Birmingham, with a tax-free stipend of £20,780 per year.

This project is co-sponsored between digilab, FOSTER Industry PhD Scheme, and University of Birmingham, with the project being industrially co-supervised by Dr Andy Corbett and Dr Cyd Cowley from digilab.

References:

https://doi.org/10.1016/j.matchar.2025.115529
https://doi.org/10.1016/j.actamat.2019.01.006
https://doi.org/10.1016/j.matchar.2025.115524

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