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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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input needs, accompanied by a boost in algorithmic development, e.g., multi-modal learning, transfer learning, federate learning, and knowledge embedding, etc. However, a significant motivation of
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of advanced computational techniques. This research will integrate power system modelling, optimisation algorithms, and artificial intelligence (AI) techniques to develop an innovative framework for strategic
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. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
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abort (or not engage) if the bright white lines that fit a defined and rigid expectation are not clearly visible. These systems use algorithms, rather than AI machine learning, to detect road markings and
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leverage low-precision accelerators for scientific computing by using a number of tricks, known as "mixed-precision" algorithms. Developing such algorithms is far from trivial. We can look at computational
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in