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and travel Requirements The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming
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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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refer to: https://www.cst.cam.ac.uk/admissions/phd ). If the candidate registers as a full-time PhD student at the University and studies for the degree, the candidate may apply to pay staff rate tuition
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PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently
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will also use finite volume-based numerical simulations and (if desired by the student) mathematical modelling. You will work alongside other researchers within the Fluid Dynamics Research Centre
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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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equivalent in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the
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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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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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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