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event-based cameras. 2. Developing the first-ever AI/ML algorithm to predict the transition in real time. This will be implemented in benchmark transient multiphase flows, such as bubbly flows, turbulent
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on high-fidelity modelling and test data for both metals and thermo-set composite materials. To achieve this we will explore the use of advanced genetic algorithms and/or Artificial Intelligence (AI
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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of hardware and control algorithms for real-world applications. The Electrical Power Group is expanding rapidly with ambitious plans. We work closely with leading industry partners across multiple sectors and
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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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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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(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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optimisation and learning-based control algorithms that can make decisions under uncertainty, using realistic network models and large-scale simulations. These methods will be evaluated on representative UK
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-of-the-art simulation algorithms to circumvent the slow dynamics leading to high-quality modelling of currently inaccessible experimental quantities. About HetSys: Harnessing Data, Modelling and Simulation