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the large-scale deployment of hydrogen. Central to the performance of these systems is the ion-conducting membrane, which governs ionic transport, efficiency, durability, and operating conditions. Currently
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plausible land-use changes, with uncertainty explicitly represented to evaluate robustness rather than single-point forecasts. Third, a preference-learning reinforcement learning agent will propose
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planting and irrigation. The work will inform restoration decision-making, connect with wider research in the TESS Lab, and includes the option of an extended visit to Saudi Arabia for field learning and
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fees are eligible to apply. However, please note the following: The award covers only part of the international tuition fee, approximately £26,000. It does not include a stipend for living expenses
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Remanufacturing plays a vital role in enabling sustainable and circular production systems by recovering value from end-of-use products and components. A key operational stage within remanufacturing
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phase of electronic neural networks is highly power-intensive, and their widespread use puts ever-increasing pressure on global energy infrastructure [1]. Photonic circuits guide and process light-based
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over time. Building on these findings, the project will quantify how different patterns of missingness may impact risk prediction model performance and calibration. Novel methods will be developed
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Join us in the University of Exeter’s Centre for Metamaterials Research & Innovation – the heart of the UK Metamaterials community. You’ll be part of the £20 million EPSRC MetaHUB – the UK’s largest
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, networking and sensing. Photonic integrated circuits (PICs) are the optical equivalents of electronic chips. Microscopic waveguides guide light across a chip to perform a multitude of functions — at the speed
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, they are computationally expensive and difficult to deploy in resource-constrained healthcare environments, and they often function as “black boxes,” producing predictions that are hard for clinicians to interpret or trust