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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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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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. Focusing on adaptive intelligence, which blends human creativity and machine intelligence, the project will develop Multi-Intelligence Agents (MIAs) to facilitate the seamless integration of social factors
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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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. 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
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. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport