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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 2 months ago
support UK industry to reach net zero. Alongside their research, our PhD researchers gain valuable training in how to apply their research within the wider industrial system, including opportunities
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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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Cyber-Physical Power Systems Research area and project description: This is an exciting PhD project to be carried out in close collaboration with a UK electrical network operator and an industrial co
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship fully-funded by the University of Exeter and National Grid to commence on 01 July 2025 or as soon
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Leads through to international knowledge and expertise of international partners and networks. The All-Wales Academy for Innovation in Health and Social Care welcomes applications for Postgraduate
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at Cranfield which has a strong collaborative history with industry in the field of atmospheric icing science research. This programme provides the PhD candidate with an outstanding opportunity to work across a
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The successful candidate will work in a highly interdisciplinary environment as part of a vibrant cohort of HDR UK-funded PhD students, with outstanding networking opportunities with fellow students
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for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer