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-based structural integrity model, validated using synchrotron X-ray microtomography and phase contrast imaging, to predict the lifetime of UK’s advanced gas-cooled reactors fuel cladding in storage
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Your job Do you want to use your passion to scientifically address challenges in (precision) agriculture and spray technology in relation to crop protection by data analysis and modelling? Do you
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systems, enabling global scalability and accessibility. Using advanced computational fluid dynamics (CFD) approaches, the project is aimed at advancing modelling capabilities for the prediction of energy
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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Generative machine learning models have made significant progress in recent years. Typical examples include, for example, high-quality image or video generation using diffusion models (e.g
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numerical modelling framework to simulate how light and heat interact with the target body tissue, while also incorporating neural signalling dynamics to explore how light-based stimulation affects
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outside of Sweden, for example a 4-year bachelor's degree is accepted. Strong knowledge of hydrodynamics, CFD, turbulence modelling, and structural mechanics. Understanding of the numerical methods behind
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Identifying and validating models for complex structures featuring nonlinearity remains a problem at the cutting edge of structural dynamics, with applications ranging from civil structures
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not fully capture the high-temperature, complex thermal-fluid interactions within the pebble-bed. This PhD project will focus on advancing porous media models for pebble-bed HTGRs by leveraging newly
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address Dr Chunwei Xia: c.xia@leeds.ac.uk Co-supervisor’s full name & email address Professor Zheng Wang: z.wang5@leeds.ac.uk Project summary Large Language Models (LLMs) have profoundly transformed the way