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: 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. Funding Notes This project is only for self funded students. View DetailsEmail
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Statistics and AI for Engineering and Smart Manufacturing School of Mathematics and Statistics PhD Research Project Competition Funded Students Worldwide Dr Wei Xing Application Deadline
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improve the robustness or responsiveness of vaccine supplies, but how do we decide whether such investments are ‘worth it’? This PhD will use mathematical and economic modelling within a multidisciplinary
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Engineering, Bioengineering, General Engineering, Applied Mathematics or Physics (at least a UK 2:1 honours degree, or its international equivalent). Knowledge, skills Strong programming skills in Python
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fluid flows and computational fluid dynamics - Deposition from chemically reacting flows - Formulating mathematical models for deposition modelling - Numerical optimisation methods - Programming for high
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. The candidate will require a first class or upper second class honours degree with strong mathematical skills in Engineering, Physics, Mathematics or similar discipline. Funding Notes This studentship covers
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dynamical systems picture of wall-bounded turbulence. The problem will be tackled with a combination of state-of-the-art advanced mathematical tools and numerical simulations, and the new understanding
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Dark Matter Search with ADMX and the Quantum Sensors for the Hidden Sector Collaboration Department of Physics and Astronomy PhD Research Project Competition Funded Students Worldwide Prof E Daw Application Deadline: Applications accepted all year round Details This Ph.D. project involves...
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. Applicants should have (or about to receive) a degree in engineering, physics or applied mathematics that is at least a UK 2:1 honours grade or its international equivalents. Previous experience with coding
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. The problem will be tackled using advanced mathematical tools combined with state-of-the-art numerical simulations and modern data-driven/machine-learning techniques. Different relaminarisation (i.e