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Field
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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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on performance and safety, for example, through the efficient computation of Lyapunov and barrier functions, forward and backward reachable sets, optimal value functions etc. The broad goal is to build upon recent
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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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) publication at top tier ranked international conferences and journals in Computer Science. Person specification: MSc in Computer Science or AI (minimum of 2:1 degree or higher) UK home student status holder
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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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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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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
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Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name & email