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application, polygraph data capture and analysis has received limited systematic research and does not yet incorporate modern sensors, computing and analytical techniques. Project: This project aims to explore
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-time sensing, multi-sensor fusion, and intelligent algorithms can jointly enable safer, greener, and smarter rail operations. Key research topics include eco-driving, environment cooperative perception
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environment-specific algorithms and machine learning approaches. At the end of the project a technology demonstrator will be built using UAV- and USV- mounted radar sensors, and it will be tested in real world
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Bragg sensors. Demonstration for evaluating the developed snake robot and its navigation and localisation strategies. We are seeking talented candidates with: First or upper second-class degree in
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-Time Structural Health Monitoring (SHM): Sensor-integrated ML models will be developed to analyze real-time data from installed wind turbine towers, enabling early fault detection and predictive