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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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optimisation algorithms to dynamically reconfigure the substation/distribution network settings to enhance the system efficiency. The optimisation algorithms will incorporate the uncertainties associated with
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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will develop autonomous on-board guidance algorithms for space missions using open-source numerical solvers for convex optimisation developed at the University of Oxford. The focus will be on designing
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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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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quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with biological datasets. Background and work knowledge in statistics, algorithms, optimization of novel
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. These problems have been compounded by the emergence of Artificial Intelligence. New forms of algorithmic manipulation have been used to sow discord in democratic societies, undermine trust in politics, and erode