267 engineering-computation-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Nottingham
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About the role As part of our annual Faculty of Engineering Apprenticeship Training Programme, we have an exciting opportunity for an advanced Level 4 Electronics & Teaching Technical Apprenticeship
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environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs
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(particularly cognitive or applied psychology) Cognitive Science Human–Computer Interaction Engineering or Computer Science Health sciences Experience in empirical research, experimental design, data analysis
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strategic National Research & Innovation Centre that brings together the UK chemicals industry, academic researchers, and policy makers to advance technology solutions that strengthen UK chemical capability
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This exciting opportunity is based within the Advanced Materials Research Group at Faculty of Engineering to conduct cutting edge research into upgrading novel biomass feedstocks with industrial
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, Computer Science and the Biosciences. You will be supervised by Amanda Wright (Optics and Photonics Research Group, Faculty of Engineering), Mike Somekh (Optics and Photonics Research Group, Faculty
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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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individual with a 1st or a 2:1 degree from Mechanical, Manufacturing, Mechatronics Engineering, Computer Science or other relevant field. The candidate should have excellent analytical and communications
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engineering excellence needed for the aerospace sector. In this PhD, high-fidelity two-phase Computational Fluid Dynamics (CFD) methods will be used to model complex and fundamental cryogenic hydrogen flows
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working with Johnson Matthey, but aligned with the EPSRC funded Programme Grant “Dialling up performance for on demand manufacturing” (EPSRC reference: EP/W017032/1). Our vision is to create a toolkit and