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Field
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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cardiovascular image analysis, but they are limited by their dependence on large, expert-annotated datasets, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where
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, which rely on rigid links and localized interaction points, soft robots are composed of deformable materials that can conform to complex geometries and operate safely around humans. They offer unique
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across infrastructure networks, studying how infrastructure administrators handle uncertainty and complexity across multiple organisational levels when managing their infrastructure assets. The candidate
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sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
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of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical
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trunk around an object. Unlike traditional robots, which rely on rigid links and localized interaction points, soft robots are composed of deformable materials that can conform to complex geometries and
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strong interest in animal behaviour and insect ecology. Specific requirements are: Strong analytical and quantitative skills, with the ability to work with complex behavioral datasets Proficiency in
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-organising reaction networks and the emergent complexity in such systems form powerful reservoir computers capable of non-linear classification, times-series prediction and forecasting, on a par or even
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of Real Estate and Construction, Faculty of Architecture focuses on transformative sustainability science and climate change research and cutting-edge innovations by gaining insights into complex human