64 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" "St" "University of St" PhD positions at University of Nottingham
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world-class training programme combining research-led innovation with real-world industry application. Students will receive high-level entrepreneurial training provided by Haydn Green Institute, bespoke
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. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral
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with our Postgraduate Research Society (PGES) and our PGR Research Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme
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for fusion components. This framework foresees two building blocks: high-fidelity Computational Fluid Dynamics (CFD) simulations of boiling flows within complex geometry using opensource software and cutting
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overall theme of this PhD programme is investigating how population-level public health policies in the UK may contribute to declines in dementia incidence. This PhD studentship is embedded within an NIHR
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overall theme of this PhD programme is investigating how population-level public health policies in the UK may contribute to declines in dementia incidence. This PhD studentship is embedded within an NIHR
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computational solid-state physics/ chemistry. Candidates with experience in the synthesis, the characterisation and performance testing or modelling of metal hydrides, complex hydrides and/or their composites
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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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one of the world’s leading centres for additive manufacturing research and development, invites applications for a fully funded PhD programme. Metal additive manufacturing is transforming how complex
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling