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industries: in-car systems, medical devices, phones, sensor networks, condition monitoring systems, high-performance compute, and high-frequency trading. This CDT develops researchers with expertise across
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capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
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achieving Net Zero by 2050. In partnership with Plant Health at Defra (Department for Environment, Food & Rural Affairs), this project introduces a novel AI-driven framework to protect the nation’s plant life
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the Internet of Things (IoT), where networked sensors and actuators enable real-time adaptation to environmental changes. Consider a self-adaptive IoT network such as a smart home that autonomously manages
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
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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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operating filters. Quantify operational performance including headloss recovery, filtrate turbidity, biological stability and lifecycle carbon—using high-resolution sensor data and life-cycle assessment tools
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scintillator-based radiation sensors combining multiple materials with complementary functions, offer a promising route to overcome these limits and achieve unprecedented timing resolution (sub-70ps), enabling