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– it is ranked in the global top 30 for seven subjects, is first in Hong Kong for three subjects, and is in the global top 100 for 26 subjects. For further details about the University, please visit
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, lack of transparency, safety assurance, and sustainability. You will work at the forefront of AI research, exploring formal and dynamic verification methods, explainable AI, and data space integration
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languages (C,C++, Python) Knowledge of offensive security Good scientific writing Involvement in the preparation of articles for publication in scientific journal(s) Data analysis skills Knowledge of advanced
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. The successful student will join the internationally recognised Sport Surfaces Research Group, with academics and researchers working across projects in sports surface safety and performance.The research group is
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volatile international security environment characterised by the return of great power competition, the Freeman Air and Space Institute (FASI), King’s College London, is seeking applications for a fully
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
generate vast amounts of operational and maintenance data, much of it remains fragmented and underutilized. Unlocking insights from this unstructured data could enable earlier fault detection, improved
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the UK Health Security Agency (UKHSA). This studentship is funded by the NIHR as part of EPR-HPRU between the University of Birmingham and UKHSA. In addition to the extensive training offered to all PhD
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Overview: Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA
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human behaviour, influenced by people’s social connections, and resources. Predicting disease spread is difficult due to factors like parent’s age, ethnicity, socioeconomic status, and nursery layout
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, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify