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placement within Siemens Digital Industry Software. Project Overview The project focuses on developing and integrating ML techniques to enhance wall treatments for under-resolved boundary layers in
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simulation, composites manufacturing and advanced sensing techniques. The project will provide opportunities to develop skills in these areas and contribute to the development of the next generation composite
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bridges and buildings by developing innovative, high performance protective columns. The proposed system features a composite column consisting of an outer Fibre Reinforced Polymer (FRP) tube, an inner
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funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description This project develops advanced simultaneous wireless information and power transfer technologies (SWIPT
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digitisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture
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Institute for Industrial Mathematics ITWM, we see our task as further developing key technologies, providing innovative impetus and implementing these in practice together with industry partners. In doing so
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resilient. The PhD student will undertake a full research programme: interviewing participants, leading focus groups, designing studies, analysing data, developing models, designing technological, educational
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affairs programming and enthusiasm for developing skills more widely in related research areas, such as cultural histories of South Asian peoples in Britain. Applicants should be able to demonstrate
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digital twins with quantified uncertainty. This project will develop a measurement-science-driven digital twin framework for energy assets, initially demonstrated on PV modules/fields and battery systems
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undertaking study in: Accounting and Finance Anthropology, Media and Performance Arab World Studies Architecture Business and Management Chinese Studies Criminology Development Policy and Management Digital