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student with an aerospace, mechanical engineering, or physics background. Experience of experimental and computational modelling of icing physics, instrumentation and imaging techniques would be
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Mobility allowance - £5,507 per annum Family allowance - £6,058 per annum (if applicable) Full-time: 35 hours per week Fixed-term: 3 Years The Opportunity: This PhD position on Physical Properties
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engineering, medical physics, image analysis, computational neuroscience or quantitative psychology is desirable. If you would like to work on a PhD project about biological understanding of human diseases and
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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satellites, with the potential for travel to test instrumentation in ideal locations. Additionally, the simulation work will focus on developing computational models to validate instrumentation and optimising
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backgrounds to join our community. At the Department of Applied Physics, our pioneering research in physical sciences creates important industrial applications that hold great technological potential. Our
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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physics background. Experience of experimental and computational modelling of icing physics, instrumentation and imaging techniques would be an advantage. Funding The Centre of Propulsion and Thermal
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may be possible, please contact Dr Mark Whiting once deadline passes. You will need to meet the minimum entry requirements for our Engineering Materials PhD programme. Candidates must meet Surrey