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engineering or a relevant area. An MSc degree and/or experience and good knowledge in gas turbine theory, thermodynamics, Machine Learning, and computer programming will be an advantage. Funding Sponsored by
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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water. The successful candidate will work collaboratively within a dynamic team, utilizing cutting-edge technology to create user-friendly sensors for deployment by citizen scientists. The project will
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utilise numerical techniques including the finite element method to describe biofluid flow and deformation in the human brain tissue. Parameters are inferred from clinical data including medical images
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evaluation. Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life (RUL) of a system. It is also a key technology for an integrated vehicle
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Cranfield’s Advanced Vehicle Engineering Centre is inviting applications to study for a PhD in battery modelling and management for electric vehicles. Several projects are on offer, covering
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years EligibilityUK, EU, Rest of world Reference numberSATM450 About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university that is a
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operability, including prediction of critical phenomena such as water hammer. The methodology will be verified against industrial data regarding performance and operation. You’ll join a multidisciplinary team
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engineering, computer science/engineering, applied physics/mathematics, or related fields. Prior experience in computer vision would be beneficial but not essential; determination, curiosity, and a willingness
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numberSATM533 Entry requirements Applicants must have a B.Sc. in electronic / information engineering or computer science and must either have or close to having a Master’s degree (must be completed by the time