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collaborators. Tasks include formulating optimisation problems, developing algorithms for optimisation with Bayesian models, and implementing solutions in relevant software. Further tasks include the formulation
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will develop and evaluate fault detection and fault location algorithms for these systems. The project is funded by GE Vernova under a wider collaboration with Imperial College London. You will be co
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development of wide bandgap device-based integrated motor drives, advanced control techniques for next-generation drives, and innovative approaches to reducing passive components in electric drive systems. Your
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of Health Informatics as part of a group of over 30 researchers using clinical data to improve our understanding of disease and the effectiveness of treatments, and implementing AI algorithms to deliver safer
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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(Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI workloads demand high performance processing, large scale data handling, and specialized hardware accelerators
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therefore paramount, but traditional simulations are plagued by the same slow relaxational dynamics. Through collaboration across Engineering, Statistics and Chemistry, this project will develop state
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not originally designed to manage large numbers of flexible and decentralised energy resources. This PhD project will develop new AI-driven methods for operating smart distribution networks so that
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% STFC:25% UoW split), gaining experience in algorithm development, experimental validation, software engineering, and scientific communication. Training opportunities include international workshops
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Integration: This WP develops a Runtime Assurance Layer by deploying lightweight anomaly detection algorithms, such as autoencoders, to flag unsafe AI decisions. It also involves the development of an Ethical