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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which
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deployments. Candidate Requirements Applicants should have (or expect to receive) a UK 1st class, 2:1 or equivalent in electronic engineering, physics, or a closely related discipline. Experience with
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be awarded a master’s degree in any of the following disciplines: Chemical Engineering, Physics, Mechanical Engineering, Energy Engineering, Environmental Engineering, Computer Science, or other
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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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multiscale metamaterials with sub-200 nm resolution. The research spans fundamental optical physics through to applications, and the student will develop skills in electromagnetic simulation, nanofabrication
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doctoral training programme dedicated to academic research in space propulsion. R2T2 PhD programmes are already underway at nine UK universities, and the programme overall is centred on the Westcott facility
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programme . This project is suitable for a student with a first-class degree in engineering, chemistry, physics or a closely related physical science. How to apply Applications should be submitted via
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, spanning domains from automotive and avionics to healthcare, increasingly rely on distributed and multi-layered control architectures. These systems comprise interconnected computing nodes, actuators and