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Field
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role involves designing and integrating real-time software algorithms with robotic hardware, including perception, control, communication, and safety modules to enable safe, precise, and reliable remote
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composite manufacturing). The research will involve developing analytical and numerical modelling approaches, sensor and experimental design and instrumentation, and developing advanced data analysis
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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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Lyudmila Mihaylova Application Deadline: Applications accepted all year round Details This PhD research is focused on multi-sensor data fusion for decision making. The project aims at dealing with large
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Details A brain-computer interface (BCI) provides a direct communication pathway between a human brain and an external device. Using appropriate sensors and data processing algorithms, a BCI maps patterns
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Silicon Sensor Particle Detectors for the Upgrade of the ATLAS Experiment and other Detectors at the CERN LHC
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grant held between biologists at the University of Liverpool (Samantha Patrick and Ollie Padget) and micro-sensor engineers the University of York (Chun Zhao and Martin Trefzer) aiming to understand
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grant held between biologists at the University of Liverpool (Samantha Patrick and Ollie Padget) and micro-sensor engineers the University of York (Chun Zhao and Martin Trefzer) aiming to understand
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drone detection and localisation performance using radar systems. This can be achieved by improving the detection performance of individual sensors and by employing a cooperative network of sensors which
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with UAVs for tackling wildfires, including modular, scalable methods with respect to the volume of collected data, to the number of UAVs, data sampling rates, number of sensors, centralised