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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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of Cambridge. The position will be for 12 months from the 2nd February 2026 in the first instance. Project research topics must fall under the combined themes of human-computer interaction and critical
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Armed Forces, critical military studies, lobbying, defence spending, etc.). This PhD studentship is only available to UK/Home students. Details of the post This studentship will commence in October 2025
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. Alternative approaches are graph-based molecule reaction space sampling and generative machine learning as they provide a path to new synthetic data that can form the basis for a large-scale database of
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become the bottleneck in achieving optimal performance and trustworthiness. This project will focus on how a federated multi-task learning framework can be effectively designed and optimised to address
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Short overview of PhD opportunity The PhD studentship aims at studying and developing more comprehensive user interfaces for computer-aided decision-making processes, which can benefit from 3D/360
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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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learning models, especially when new training experiences are corrupted. The framework will be validated in robotic control scenarios during EV battery assembly. As a PhD student, you will work with both