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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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Research Studentship in ‘Deformation and fracture of TRISO fuel particles’ 3.5-year DPhil studentship Supervisor: Prof Dong Liu, Prof Emilio Martinez-Paneda About the Project The proposed PhD
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(R2T2) program and is an integrated doctoral programme, run across eight UK universities, which seeks to provide the opportunity to pursue a PhD in space launch technologies. Please see r2t2.org.uk
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to reduce AC losses and boost power density. Today's modelling tools are not yet equipped to fully explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers
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(£20,780 for 2025/26). How to apply: To apply click Apply for a Programme via the above ‘Apply’ button, create your account, and use the link sent by email to start the application process. Please select
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
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desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate collaboration within interdisciplinary research teams. Application Process: To apply
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motivated applicant to undertake an original and applied programme of research linked to ongoing work led nationally by the Chartered Institute for the Management of Sport and Physical Activity (CIMSPA
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in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the