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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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disciplines to contribute to world-changing research in the development and deployment of trustworthy AI. The scholarship programme is part of the University’s internationally recognised Cyber Security Global
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Apply online, by clicking the 'Apply' button, above. Select programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time
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workshops.The PhD students will focus on using state-of-the-art computational and statistical techniques to shed light on the fundamental mechanisms of decision-making.We are particularly interested in candidates
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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Photovoltaic (PV) power is crucial for advancing global energy sustainability, as it harnesses abundant and renewable solar energy to generate clean electricity with minimal environmental impact. By converting sunlight directly into electricity, PV systems decrease greenhouse gas emissions,...
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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Deadline: All year round How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5-year PhD project is open to home students; the successful candidate will receive an annual tax free stipend based on the UKVI amount (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend...
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will