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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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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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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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Discover your career The world of the University of Nottingham is defined by our people and the values we share. Our environment is an ambitious vision brought to life across vibrant and forward-thinking global campuses. An ever changing world where open minds and diverse cultures are able to...
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cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects available and how to apply, please visit: http
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At the Mixed Reality Laboratory, School of Computer Science, University of Nottingham Closing date: 28th March 2025, interviews will take place in April and May Department: Computer
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Applications are sought for a fully-funded 42 month PhD studentship to work with Dr Rachel Nicks and Prof Stephen Coombes on the project: White Matter Computation: Utilising axonal delays to sculpt
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics