668 web-programmer-developer "https:" "https:" "https:" "https:" "https:" "https:" "University of Kent" PhD positions in United Kingdom
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interact without full trust in a centralized party. This research project aims to develop cryptographic solutions and frameworks that secure AI systems, particularly in decentralized and distributed settings
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, analyse learning from past incidents and exercises, and co-develop practical frameworks or tools to support improved cross-agency working. These will be tested through scenario-based evaluation and
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funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description This project develops advanced simultaneous wireless information and power transfer technologies (SWIPT
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, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning
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(SRM) may be deployed to counteract harmful effects of climate change. However the impacts of SRM on (eg) monsoons, extreme weather, and air quality are poorly understood. We seek to develop and apply
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Recent advances in artificial intelligence (AI) have fuelled the idea of building “AI scientists”, i.e., systems that can perform part or all of the research process on their own. The development
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digital twins with quantified uncertainty. This project will develop a measurement-science-driven digital twin framework for energy assets, initially demonstrated on PV modules/fields and battery systems
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
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together to answer some of the most important questions about the causes, prevention and treatment of disease. We are seeking a Senior Researcher to take the lead in the development of statistical and
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this challenge by developing modern data driven tools that help predict and manage corrosion in next generation bio refineries. The project brings together leading researchers from University of Leeds