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Field
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machine learning (applied to spatiotemporal data). International and UK applicants are both eligible to apply. Sponsor: This scholarship is funded by the UK Engineering and Physical Sciences Research
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1st class degree in Engineering with strong background in theoretical and computational mechanics of solids/materials. To apply please contact the supervisor, Prof Andrey Jivkov - andrey.jivkov
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technology is emerging as a key commercial fusion solution promising pilot plant concepts that can be deployed by the 2040s. Tokamak Energy, a leading private fusion company in the UK and the UK Atomic Energy
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spherical tokamak with high-temperature superconducting (HTS) magnet technology. However, the compact design of a spherical tokamak places the fusion plasma in close proximity to a critical component known as
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, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. To apply please contact the supervisor, Dr Jane Wood - jane.wood-2
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the coordination guarantees. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Candidate
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maths, physics, mechanical or materials engineering or a closely related discipline is essential. A Masters-level degree or publication record in any of the above fields would be advantageous. Good
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summary The PhD studentship will broadly explore development of cutting-edge AI solutions for image registration, anatomy segmentation, and immersive technology. The selected candidate will work with
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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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responsibilities — between countries, regions, and generations — are emerging as key concerns in both academic and policy debates. This PhD will explore how different CDR approaches — including engineered options