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slow sand filters. This project suits graduates seeking careers in drinking water technology, sustainable infrastructure, and low carbon process design. Drinking water production is under mounting
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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to realise their full potential, from academic achievement to mental and physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science
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policymakers. Entry requirements Applicants should hold or expect to achieve an equivalent of a first or second-class UK honours degree in materials science, physics, engineering, or a related discipline. The
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to realise their full potential, from academic achievement to mental and physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science
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knowledge co-evolution and addressing complex challenges in a super-intelligent society. This project is situated within the rapidly evolving field of Cyber-Physical-Social Systems (CPSS), which is of
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support our staff and students to realise their full potential, from academic achievement to mental and physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example
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community. We welcome students and staff from all backgrounds from over 100 countries and support our staff and students to realise their full potential, from academic achievement to mental and physical
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate