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The Surrey team has recently demonstrated the performance of new perovskite scintillator materials which combine a high scintillation light yield, high material density, good optical transparency
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Autonomous vehicles (AVs) are advancing rapidly, yet their safety assurance remains limited by the opacity of modern AI systems. Current machine learning–based decision pipelines often function as
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reducing odours from pomace and digestate. The project comprises seven work packages. As a leading partner, the University of Surrey will develop a system digital twin (SDT) to enhance overall sustainability
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to manage and lead independent work within a larger team Demonstrates initiative and creativity in problem solving Commitment to diversity, equity and inclusion Ability to adhere to safety protocols and
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applications. Understanding durability requires research into the effects of both manufacturing methods and environmental storage conditions on the material properties and performance over time. The aim
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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be selected. The candidate must meet the minimum requirements for our PhD programme. Applications will be considered on a rolling base. How to apply Applications should be submitted via the PhD Physics