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The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship co-funded by the partner Hydro International and University of Exeter Faculty of Environment
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detection. The successful candidate will engineer selective surface chemistries, advance flow-through detection methods, and apply the sensor to mechanistic studies of PFAS interactions with proteins and
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these into game engines to visualize and provoke alternative, sustainable working environments that make space for nature. The student will consider how digital-twinning (virtual replication) and gamification
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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Photovoltaic (PV) power is crucial for advancing global energy sustainability, as it harnesses abundant and renewable solar energy to generate clean electricity with minimal environmental impact. By
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of the GDPR, Federated Learning (FL) has emerged as a leading privacy-preserving technology in Machine Learning. Despite its advancements, FL systems are not immune to privacy breaches due to the inherent