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critical, to ensure expected engine performance is achieved. To predict this complex flow and heat transfer, next-generation Computational Fluid Dynamics (CFD) solvers using Large-Eddy Simulation (LES) and
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seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking
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Engineering and Analytical Science Civil Engineering Computer Science Electrical and Electronic Engineering Management of Projects in Engineering Mechanical Engineering Academic requirements To be considered
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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techniques. We are a community based on mutual support and collaboration. Through our Doctoral College there are continual opportunities for building important research skills and networking among your peers
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applicant must have (or be close to obtaining) a relevant PhD in Fluid Mechanics from an Engineering, Mathematics or Physics Department, a strong background in theoretical and computational fluid mechanics
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. The project will be part of the activities of the Constellium University Technology Centre (UTC) established with BCAST. The successful candidate will have the opportunities to interact with researchers in