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the need for sustainability to achieve Net-Zero goals. Cyber-Physical Systems (CPS) integrate machines, robots, and AGVs, but challenges like mechanical wear and electronic errors pose risks to efficiency
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to the new theoretical development of graph deep learning, and contribute to the research community of brain connectivity and network neuroscience. This is a joint Phd studentship between Coventry (UK) and
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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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significantly reduce carbon emissions and bolster global efforts to achieve net-zero targets. Despite considerable advancement in their operational performance, their life cycle impacts, including raw material
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Automation (ICRA), ROSCon and others. This PhD offers extensive transferable skills, including expertise in robotics, navigation, sensors, and system design. Graduates will be well-positioned for careers in
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PhD project (such as Electrical Engineering or Computer Science) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work
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Job Code: 9521 - Research Assistant and 9529 - PhD Candidate Research Assistant Employee Class: Grad/Prof Student Position This position will provide support for lesson plan development relating