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to support safe automation. Aim This project will focus on investigating and developing new ways in which deep learning-based solutions can continuously learn and deal with unseen situations, with a particular
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Research Group at the Faculty of Engineering which conducts cutting edge research into experimental and computational heat and mass transfer, multiphase flows, thermal management, refrigeration, energy
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in sustainable building design, building performance assessment, building energy efficiency and carbon management in buildings to join our team. Candidates must hold a degree or equivalent
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dealing with investigations on the development of bespoke high-tech laser beam processing methods for surface treatment and repair of aero-engine components. The project will deal with the study of a new
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components. The project will deal with the micromechanics and in-depth materials analysis of advanced aerospace materials upon manufacturing operations to understand the materials' response
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Photovoltaic Modelling for Performance Optimisation Theme 3: AI-Enhanced Coordination of Renewable Energy for Smarter Grid Management Theme 4: Decoding Social Acceptance: The Community Lens on Large-Scale Solar
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About the project We are recruiting applicants for a fully funded PhD studentship in the School of Chemistry at the University of Nottingham to work under the supervision of Dr David Duncan. The project