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Field
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Hours of work: Part-time / 0.5 FTE Tenure: Fixed term for 12 months This is an exciting opportunity to contribute to a collaborative Engineering and Physical Sciences Research Council (EPSRC)-funded
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performance; academic literature has lagged commercialisation, and currently disseminated studies only scratch the surface on this complex, multi-physical phenomena. This studentship project will seek
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with The Faraday Institution’s LiStAr programme, we will explore the development and optimization of QSS cells, including physical characterisation of degradation pathways at the anode and cathode
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provide adequate information on your academic ability, research potential, communication and engagement skills and your interest in the research topic. Full guidance on the application process is available
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at the intersection between computer science and condensed matter physics, offering the student the opportunity to work across both disciplines toward the development of next-generation computing technologies
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existing models struggle to capture this complex, multiscale phenomenon efficiently. This project will develop a novel, physics-informed surrogate model using Bayesian machine learning to predict gas
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relevant to the proposed PhD project, including chemistry, materials science, engineering or physics. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of
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, physical sciences, or a closely related discipline. We are particularly interested in candidates with: A degree in civil, mechanical, ocean, or offshore engineering, or a related discipline Interest in
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next generation of physics-based degradation models grounded in measured rather than assumed parameters. This project offers a rare combination of fundamental scientific depth and clear industrial
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partitions of unity that are unavailable in the analytic setting. We expect to apply these techniques to geometry, quantum mechanics, and other fields in mathematical physics. The project will be supervised by