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background in Computer Science, Mathematics. Students with interests in machine learning, deep learning, AI, uncertainty quantification, probabilistic methods are encouraged to apply. For eligible students
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, Aerospace and Civil Engineering at the University of Sheffield, and embark on a transformative PhD project funded by John Crane Ltd, a global leader in engineering technology. What’s the Project About
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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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the opportunity for the PhD student to lead the development of innovative simulation tools that predict Litz wire behaviour across electrical, thermal, and mechanical domains. Supported by the MTC’s advanced wire
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to exploit approximate or computational solutions; however, this can be unsatisfactory in that it lacks in valuable physical insight. This insight is often crucial in changing partial mathematical solutions
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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degree or a master’s (or international equivalent) in a relevant science, mathematics or engineering related discipline. Excellence in computational science and mathematics Programming skills in any
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in Geography, Environmental and Earth Sciences. This PhD scholarship is suitable for students with a background in oceanography/marine science, physics, physical/environmental sciences, mathematics
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in inks, surfactants added to crop sprays to improve jetting, wetting, adhesion, and bodily fluids with polymeric components. This PhD project aims to explore how such additives affect micromechanics