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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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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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frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible. Multiobjective optimization algorithms will be employed to balance key performance indicators such as
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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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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Havoutis Year 1 MSc Course: MSc Robotics Year 2 – 4 PhD Location: Oxford University Research Abstract: This PhD project will focus on developing an AI-based system for multi-collaborative scouting and
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This PhD project focuses on the development of next-generation autonomous train technologies that combine energy-efficient control with advanced environmental perception. You will explore how real
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techniques, would be an advantage. The ideal candidate will have a deep interest in the algorithms that power graphics and a creative mindset, eager to think outside the box and develop novel solutions
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acquisition of a range of environmental and operational data in the digitisation of food manufacturing processes for processing using applied AI techniques. We anticipate the successful applicant will develop
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manufacture, to enable quantitative imaging. Your research will include a mix of computational and experimental work to develop and characterise these instruments. Monte Carlo simulations (using GEANT4) will