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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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-generation defensive capabilities. The project focuses on moving beyond siloed detection methods to create a unified, multi-modal framework for identifying AI-generated threats. Its core aim is to develop a
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The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global
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Targeting Cardiometabolic Dysfunction in Heart Failure with Preserved Ejection Fraction (HFpEF): Mechanisms of Exercise-Induced Protection Overview Applications are invited for a fully funded 4-year
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access to advanced sequencing platforms and collaborative support from genomics and bioinformatics core facilities. The student will build computational pipelines for multi-omic integration across
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a comprehensive, multi-fidelity suite of liquid hydrogen (LH2) pump models to predict and analyze pump performance, stability, and its interaction with the broader fuel system architecture for a
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staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon
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weights. We simply wrap it with a clever layer of reasoning and evaluation. It’s like giving the AI a strategic co-pilot that helps it think ahead without changing its core personality. Why This Matters
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. This project leverages and advances these trends, targeting the development of multi-functional coatings to enhance EV battery safety. This PhD will design and characterise intumescent, dielectric, lightweight
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research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture