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studentship will broadly explore development of cutting-edge AI solutions for image registration, anatomy segmentation, and immersive technology. The selected candidate will work with preoperative MRI/CT scans
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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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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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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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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
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). The AI DTC is an initiative by the University of Nottingham to develop future researchers and leaders who can address key challenges of the 21st century through foundational and applied AI research
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for devices containing quantum materials. The project addresses this gap by developing measurement protocols which test the Hamiltonian hypothesis and hence support the materials discovery process. [1] E. Lupo