276 computer-programmer-"https:"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" positions at University of Nottingham
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are invited for a fully-funded Industrial Doctoral Landscape Award, offered in partnership with Rolls-Royce, to tackle key challenges in the design of aeroengine oil systems using multiphase Computational Fluid
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across epidemiology, building science, and exposure modelling — contributing to an ambitious international programme with direct policy relevance. Be part of a project that will influence how buildings
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Purpose of role: The Biochar Demonstrator is a £4.5M project funded by BBSRC as part of the £30M Greenhouse Gas Removal (GGR) programme. The Demonstrator will address the uncertainties concerning
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Medicine and Science. The work is a collaboration between Dr Pavel Gershkovich, Prof Kin-Chow Chang, Dr Leah Goulding and Prof Chris Hayes. A few years ago, we made a groundbreaking discovery of a plant
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Purpose of role: The Biochar Demonstrator is a £4.5M project funded by BBSRC as part of the £30M Greenhouse Gas Removal (GGR) programme. The Demonstrator will address the uncertainties concerning
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of Medicine undergraduate programmes including the 4-year Graduate Entry Medicine (GEM) course and our new 5-year BMBS Medicine curriculum which launches in September 2026. You will be expected to create new
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Project (Nov 2027), whichever comes first. This post is full time (36.25 hours per week). Please contact Dr Marco Raczka on marco.raczka@nottingham.ac.uk if you have further questions about this role
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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the network directors, co-leads, and colleagues across the partnership to manage the effective administration of the programme. The role will involve planning and management of key functions, including funding
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Centre of Excellence. This is a unique opportunity to work on advanced image analysis and image-driven modelling as part of a wider multi-disciplinary programme that includes mathematical modelling, cancer