74 professor-computer "https:" "https:" "https:" "https:" "https:" "Dr" "University of Aberdeen" PhD positions at University of Nottingham
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with a 1st class degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http
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Supervisors: Dr Negar Gilani and Professor Richard Hague The Centre for Additive Manufacturing (CfAM) Research Group within the Faculty of Engineering at the University of Nottingham, recognised as
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. Gordon Airey, Dr Anand Sreeram, Dr Nick Thom, Dr Richard Taylor Programme length: Four years (full‑time) Start date: 2026/27 academic year Keywords: biogenic supply chains, sustainable materials, biobased
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Studentship Information Supervisor: Professor Ian Fisk Secondary Supervisor: Dr Vincenzo di Bari, Dr Louise Hewson, Mui Lim Subject Area: Food Science Research Title: Sodium Reduction in Coated
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autonomous systems. Supervision The project will be supervised by Dr Anthony Siming Chen (EEE), with co-supervision from Professor David Branson III (M3) and Professor Praminda Caleb-Solly (Computer
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appraisal, to ensure that design choices do not undermine the sustainability imperatives driving the transition to green-fuel propulsion in the first place. Research Aims This PhD programme addresses
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Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career
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, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http://www.nottingham.ac.uk/pgstudy/apply/apply-online.aspx For any enquiries about the project please
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Dr Luisa Ciano, Dr Anca Pordea and Dr Rob Holland Application deadline: 07/04/2026 Starting date: Oct 2026 Funded PhD project (UK students only) Vision We are looking for a highly motivated PhD
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The rapid growth of deep learning has come at an extraordinary environmental and computational cost, yet the standard training paradigm remains remarkably unchanged. Every sample is passed through