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Field
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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on developing a novel AI-powered conversational
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pressure to reduce both energy demand and chemical consumption. Project SandSCAPE, an Ofwat-funded programme, tackles this challenge by integrating purpose-built robots that skim slow sand filter beds while
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with: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in
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alloying elements from the OBMs like V and Mn (which depends on the iron ore sources) will be distributed between the steel, slag and dust during EAF steelmaking. The presence of these residual elements in
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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select 'Mechanical and Manufacturing Engineering' under ‘Programme’. Please quote the advertised reference number, ‘FP-CTS-2025’, under the ‘Finance’ section of your application. Please note that 1 January
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This 4-year PhD programme is fully funded for home students; the successful candidates will receive a tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid
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, computing, and energy economics. The successful candidate will have an excellent understanding in one of the following fields: power system operations, power system economics, linear programming, micro
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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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R2T2 is a UKSA-funded doctoral training programme dedicated to academic research in rocket propulsion, with an emphasis on the acquisition of the practical skills required to pursue a career in the