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elements like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) to secure hardware components. Embedded Trust Protocols: Design protocols that establish and maintain trust within
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approaches, including principal component analysis and machine learning, to handle multivariate datasets. Prior experience in data science is not essential; the successful candidate will be supported through
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paid. We expect the stipend to increase each year. Only Home students are eligible for funding. The start date is October 2026. The project aims to develop and optimize metal oxide aerogel materials
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catalysts. This EPSRC-funded project leverages cutting-edge X-ray spectroscopy to unlock how alkali elements can be harnessed to create powerful heterogeneous catalysts for CO₂ and hydrogen technologies. By
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Matlab, Python and C/C++ are preferred. Strong interpersonal skills and the capacity to work and learn independently will be required. English Language IELTS 6.0 Overall (with no individual component below
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and training activities that will contribute to developing professional networks. Understanding the growth of surface oxide films on/in multi-component metallic substrates in electrolyte media is of
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programming experience (preferably in Python). If English is not your first language, provide evidence of proficiency through: A minimum IELTS average score of 6.5 and a minimum of 6.0 in each component. OR A
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partner Tata Steel UK. The project aims to advance fundamental knowledge on the impact of residual elements inherited from steel scrap on slag performance and utilisation in the scrap-based electric arc
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models used in component scale CFD assessments. In particular, this concerns quantifying the effects of the heat transfer surface’s detailed topography, porosity and wettability on near-wall bubble
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MATLAB/Python/R etc Previous research experience with healthcare datasets or electronic health records English Language IELTS 6.5 Overall (with no individual component below 6.5) or Swansea University