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the opportunity to transition into a PhD programme based on performance and mutual agreement. The Cambridge Institute for Medical Research (CIMR) is located on the Cambridge Biomedical Campus and it is
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-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable
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trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
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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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, you’ll be developing innovations critical to a greener, more sustainable future. In hydrogen storage and transport, high-performance mechanical seals are essential. These seals prevent gas leakage by
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’. Warwick University is renowned for its high-quality research and a thriving PhD program. This strong research culture enhances both the PhD student’s experience and the demand for our graduates. This PhD
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been filled. Electrical treeing is a primary degradation mechanism in polymer insulation leading to the ultimate failure of high-voltage (HV) cables. Despite being a phenomenon first observed and studied
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additives in lithium-ion battery (LiB) electrodes. With the exponential growth in demand for high-performance batteries, the need for scalable, high-quality CNT production has never been greater. Chemical
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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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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material