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include streamlined certification processes, improved system reliability, and reduced downtime, benefiting industries such as aviation, automotive, and medical devices. By aligning with the increasing
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capable of dynamically adjusting their collaboration strategy—such as autonomy level, motion behaviours, and information transparency—based on real-time human trust. By aligning vehicle behaviour with
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welcomed to reach out to discuss their interests and tailor the research direction to align with their expertise and aspirations. Student undertaking this project will gain a wealth of experience and
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conservation. The project will engage with the UK Pollinator Monitoring Scheme (PoMS) and DEFRA’s Pollinator Advisory Group to ensure alignment with national biodiversity goals. Outcomes will enhance
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institutions. State-of-the-art facilities: Access advanced laboratories and high-performance resources. Flexible learning: Tailored research projects aligned to personal interests and career aspirations. Career
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track and classify them. This also helps to observe different angular realisations of the multipath and clutter and to measure multiple angular-dependent target Doppler contributions, decreasing
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recovery. Through real-world testing and industry-aligned development cycles, students gain practical experience in resilience modelling, embedded AI diagnostics, and autonomous recovery protocols
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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that can be validated with experiments and bottom-up models at multiple scales in order to predict the macroscopic response. Hence, this research will investigate the degradation of metallic materials under
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. The supportive, interdisciplinary environment ensures research is practical, innovative, and aligned with real-world challenges. Expected Impact? This research is expected to deliver a practical, non-destructive