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to validate the computational tools, explore the intake flow distortion, and provide guidance on the design of future intake/fan configurations. This position is part of the CDT in Net Zero Aviation, which
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, applicants should be eager to develop strong coding skills as part of the project. Ability to work both independently and collaboratively in academic and industrial settings. How to Apply Submit the following
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code based on Modified Newtonian aerodynamics and a coupled, nonlinear thermo-structural finite element solver. Supervisors: Professor Matthew Santer, Dr. Paul Bruce. Learning opportunities: You will
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the 'Apply' button, above, quoting code MPB50490525. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up
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biomedical engineering). Flexible start date! What You’ll Need A first-class or upper second-class honours degree (or equivalent) in Engineering, Physics, or Applied Mathematics. Experience in coding and CFD
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Position Summary: Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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to improve structural durability, reduce material consumption, and support the UK’s net-zero goals. Funding notes: The position includes a full scholarship for UK-based PhD candidates and a half-scholarship
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Recycling and Circular Economy" How many positions: 1 This 3.5 year PhD is open to UK nationals. The successful candidate will receive an annual tax free stipend set at the UKRI rate (£20,780 for 2025/26) and
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generally make the vehicle a special place to be. The project will treat the experience of tranquillity as a phenomenon that can be measured and influenced. Attention to design contexts and design processes