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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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, biomechanical aspects related to wearable sensing, and optimisation of sensors and wearable electronics for selected healthcare and sports applications. Your Group This project is part of the prestigious
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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
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the performance of novel, renewable, wave energy harvesting approaches. Here the research ambition is to extend the state of art from small scale sensor networks (nW’s to mW’s), towards a vehicular scale (W’s to
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with a wide network of stakeholders, and explore new avenues for medical applications. For ongoing work and publications on this project, please see our website: www.cnnp-lab.com . This is a 12-months