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EngD: Generative AI for scalable, sustainable, and trustworthy manufacturing (sponsored by Rolls-Royce)
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of the service, using internal and external data sets (e.g. curriculum data, the data that underpins regulatory compliance by the Office for Students and programme and module surveys) to help develop services
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Computational Complexity Theory
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of such program could be done in case of it was necessary. For instance, for the linkage of new material models or certain numerical features such as a new finite element. This research will benefit from excellent
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Adaptive Learning in Brain-Robot Interactions
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Advanced Carbon Fibre Composites using Next-Generation Additive Manufacturing (CFAM)
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Generalisable, Physics-Aware Machine Learning for Gas Turbine Engines
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subjected to a typical loading scenario. This research will benefit from excellent computing facilities, expertise in computer-aided engineering (CA2M lab), the available experimental facilities including
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pharmaceutics teaching within the MPharm programme ensuring that it is accessible, inclusive and contributes to the University’s Teaching and Learning Strategy. Improve and enhance the student experience and
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has on the space-time geometry. The aim of the project is to explore the backreaction of quantum fields on black hole space-times. First, the stress-energy tensor for a chosen quantum field is computed