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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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into car cabins (to reduce the exposure of occupants) and the regions where pollutants accumulate (to be avoided by pedestrians and cyclists) need to be minimised. The PhD objective is to study the effects
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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The PhD is funded by Kentown Support, a charity focused on improving community care for children with life-limiting conditions. The PhD will start in October 2025 and is funded for 3 years. Award
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PhD Studentship: Electrical Machine Architectures for Next-Generation NetZero E-Mobility. the University of Nottingham This project offers an exciting opportunity to undertake cutting edge research
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: Dr James Yates, Director GSK Aligned programme of study: PhD in Mathematics Mode of study: Full-Time Project description: HIV remains one of the most persistent and challenging infections to cure due
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enabling 3D flux paths, novel cooling strategies, and increased architectural flexibility. Aim This PhD project aims to explore and optimise new electric machine topologies that go beyond conventional 2D
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formats available in conventional hardware are often too accurate for the needs of machine learning: they do not improve the quality of the trained model but may deteriorate it by causing overfitting