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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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as to what role law should play in reducing potential harms, in helping to distribute risks and benefits across different groups in society, and in how existing (or future) legal rights and duties
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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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on: 1. Finite Element Simulations & Experimental Data Collection: High-fidelity simulations and scaled prototype testing will generate data on stress distribution, local buckling, and damage evolution. 2
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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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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
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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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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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, stress markers, EEG, and ECG — will be collected by VR headsets and IoT devices. ML algorithms will analyse this data to identify trends, project risk factors, and propose tailored treatments. By combining