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, plays a central role in the study of new gauge theories that have the potential to address many of the STFC challenges in Frontier Physics, such as the origin of dark matter in the universe, and the
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candidates from all backgrounds to join our community. At the Department of Applied Physics, our pioneering research in physical sciences creates important industrial applications that hold great technological
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disproportionate loss of muscle mass compared to conventional ‘dieting’, which can have detrimental effects on physical function. The present fully funded PhD studentships will perform a series of human physiology
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Overview You will be a member of the Particle Physics and Particle Astrophysics (PPPA) group in the School of Mathematical and Physical Sciences. We are seeking to appoint three fixed term Research
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The University’s Department of Geography invites applications for a PhD studentship funded by the Environment Agency and South West Water and the University of Exeter to commence on 22nd September 2025 or as soon as possible thereafter. For eligible students the studentship will cover Home or...
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Funding for: UK Students Discipline: Engineering & Technology, Electrical and Electronic Engineering, Other Engineering, Physical & Environmental Sciences Qualification: Doctor of Philosophy in
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representatives to drive meaningful change for the citizens of Wakefield. We would like to support a PhD candidate to undertake research in the following areas: Evaluating and understanding the process and outcomes
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the need for sustainability to achieve Net-Zero goals. Cyber-Physical Systems (CPS) integrate machines, robots, and AGVs, but challenges like mechanical wear and electronic errors pose risks to efficiency
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We invite applications for a fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is available to UK (Home) candidates only
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techniques for multivariate curve resolution, together with physics-informed AI to overcome Nuclear Decommissioning Authority (NDA) data analysis challenges. Previous machine learning (ML) uses ‘out-the-box