74 computational-physics "https:" "https:" "https:" "https:" "INRAE" PhD positions at University of Nottingham
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multidisciplinary effort to investigate the anatomical, physical and cellular factors that shape internal root environments. The project will explore how root organisation and environmental conditions combine
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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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techniques for feedstock and high value products characterization. 1st or a 2:1 in a Chemical Engineering, Mechanical Engineering, Materials Engineering, Chemistry, Physics Please contact Dr Orla Williams
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support After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process (this will cover home tuition fees and UKRI stipend) Postgraduate
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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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Physical Sciences or a related discipline, with expertise in fluid mechanics and heat transfer. Experience with Computational Fluid Dynamics software, preferably OpenFOAM. Programming skills with software
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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
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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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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
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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