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A large volume of data are routinely captured in high-performance training and competition environments. Whilst these data have the potential to inform key performance decisions, the full potential performance impact is often not realised. In some instances, this is because the volume of usable...
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., Semiclassical asymptotics for Bergman projections with Gevrey weights, arXiv: 2403.14157. Xiong, H., Generic simplicity of resonances in obstacle scattering, Trans. Amer. Math. Soc. 376 (2023), 4301-4319.
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are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description Offshore solar energy is an emerging and highly promising technology for
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Lancaster University, & Oxford Risk (London) The Department of Economics at Lancaster University Management School (LUMS) invites applications for one fully funded ESRC CASE PhD studentship
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on evidence of readiness to pursue a research degree. Applicants with a Physics, Maths or Electrical Engineering background are encouraged to apply. An ideal candidate should also have a creative problem
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will make water networks robust and resilient to these threats. Candidate requirements Starting October 2026, we require an enthusiastic graduate with a 1st class degree in engineering, maths or a
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or applied maths, preferably at master's level. A 2:1 degree can be considered for applicants with prior experience in relevant research areas. Funding This is a self-funded PhD opportunity, therefore you must
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degree in engineering, maths or a relevant discipline, preferably at master's level - in exceptional circumstances a 2:1 degree can be considered. Funding Explore funding opportunities for postgraduate
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degree in engineering, maths or a relevant discipline, preferably at Masters level (in exceptional circumstances a 2:1 degree can be considered). To apply visit: http://www.nottingham.ac.uk/pgstudy/apply
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Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing. Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths