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, and employ high-throughput computational screening and materials informatics, to identify promising candidate materials. Aim You will work with Dr Sanliang Ling and Prof Alasdair Cairns. You will have
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a variety of machine learning algorithms trained on these data and, most crucially, will develop and implement techniques for computing the uncertainty in the prediction. The algorithms developed in
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University Technology Centre (UTC) in Manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a 3-year PhD program in partnership with the UK Atomic Energy
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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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Rolls-Royce University Technology Centre (UTC) in manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership
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degree which includes a substantial research element, with a score of 65% or above in the taught modules and 65% or above in the dissertation. Complete the PhD Programme online application . Your
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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propulsion. Who we are looking for We are looking for enthusiastic, self-motivated applicants with first-class degree in electrical engineering, Aerospace Engineering or Computer Science with good electrical
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nationals only) and research costs) three-year full-time PhD available to start on the 1st October 2025. The overall theme of this PhD programme is improving clinical assessment and research access
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be