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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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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
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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methods for defect detection; Apply AI and machine learning techniques to process, analyze, and interpret complex NDE data; Create AI models for automated defect detection, classification, and
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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