50 computer-programmer-"https:"-"Prof" "https:" "https:" "https:" "https:" "https:" "U.S" PhD positions at University of Nottingham
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are invited for a fully funded Industrial Doctoral Landscape Award in partnership with Siemens Digital Industry Software, focused on advancing the next generation of industrial Computational Fluid Dynamics (CFD
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). This studentship will include a placement at Astra Zeneca, Cambridge and is part of a broader Medical Research Council Programme grant focused to understand mucus regulation in severe asthma. The project will
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of involved phases. Candidate requirements You must have very good knowledge and expertise in material physics and/or chemistry or computational solid-state physics/ chemistry Candidates with experience in
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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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student to revolutionise electrical machine design and development based on programmable 3D electrical steel technology enabled by advanced manufacturing processes and emerging magnetic materials
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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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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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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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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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materials for low-emission ammonia conversion. Perform both experimental investigations and computational simulations of the combustion process. The outcome of this project will demonstrate the feasibility