Supporting Development of Fusion Power by Developing Techniques to Understand Uncertainty in Fu[...]

Are you looking for a PhD opportunity where you can contribute to the development of sustainable fusion energy, helping to overcome a key challenge for our society and creating a green future for our world? This PhD is based in the Centre for Intelligent Infrastructure at the University of Strathclyde, Glasgow, in collaboration with the UK Atomic Energy Authority (UKAEA), who manage the UK Fusion Energy programme. The PhD is partly funded by the UKAEA’s new Lithium Breeding Tritium Innovation (LIBRTI) programme.

This exciting PhD project will focus on implementing cutting-edge machine learning techniques to the complex problem of predicting the thermal-chemical-physical behaviour of fusion reactors. The project aims to use these techniques to characterize and propagate uncertainties through existing fusion reactor models (including neutron transport and multi-physics models). In fusion, the development of reliable models of the reactor conditions are vital for ensuring that future designs are both safe and economic. Models are used to predict multiple properties including the activation of materials, the dose rates during periods of shutdown, reactor temperatures, damage to materials, tritium breeding rates, etc. These properties inform every stage of the fusion lifecycle and will be used to optimize reactor design, ensuring that reactor component lifetimes are maximised and that the dose rates to personnel during maintenance operations are minimized.

This PhD project will implement emerging machine learning techniques to propagate aleatory and epistemic uncertainty in a transparent way. It will also explore the potential use of artificial intelligence (AI) solutions to select the most appropriate approach to speed up the analysis. Nuclear Fusion reactors are on the verge of becoming a realistic prospect for low carbon energy generation. The outputs of this PhD project could play a significant role, assigning confidence levels to key reactor properties, and influencing UK and International future reactor design. Nuclear Fusion is a rapidly growing area of research, and the project will deliver excellent prospects for post-PhD employment both in industry and Universities.

The candidate is not expected to have any prior knowledge of nuclear fusion or uncertainty analysis. The successful candidate will have a first-class or upper-second-class bachelor's degree and/or Master’s degree in an appropriate science or engineering discipline. Candidates in nuclear engineering, mechanical engineering, physics, applied mathematics, computer science and all other relevant fields are encouraged to apply.

The PhD researcher will also have the opportunity to undertake a 3 to 6-month secondment at UKAEA at the Culham Centre for Fusion Energy (CCFE).

Please note we can only accept international applicants that are exempt from ATAS Clearance. This project is offered through the SATURN CDT (Skills And Training Underpinning a Renaissance in Nuclear Centre for Doctoral Training) and sponsored by UKAEA.

For further information: SATURN CDT. Candidates wishing to discuss the research project should contact the primary supervisor, Professor Edoardo Patelli at Edoardo.patelli@strath.ac.uk or specific questions on the SATURN CDT framework for PhD to saturn@manchester.ac.uk as soon as possible and by the closing date: 31st May 2025.