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working with complex data Enjoy learning beyond your current expertise with the support of our excellent interdisciplinary team Eligibility Start date: 1 October 2025 Open to applicants eligible for UK home
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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project would suit students with a background in electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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. It is essential that they are knowledgeable in current behaviour change science and techniques and specifically have experience of designing topic guides and administering in-depth, semi-structured
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from the Defence Science and Technology Laboratory (Dstl). Award value The Studentship covers: Stipend: at UKRI rate + London Weighting (£22,780 for 2025/26 academic year) Tuition fees: UK Home Fees for
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where
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entrants without historical data for their land use technology differently compared to those with established practices? This interdisciplinary project offers the chance to contribute to multiple fields
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cause of death by 2050, with novel approaches to diagnostics urgently required. This project will develop a new sensor technology to diagnose bacterial infections rapidly. The research will be embedded in
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, machine learning, and information-theoretic approaches to achieve robust, non-intrusive security for the ever-expanding IoT landscape. Feature Engineering for Encrypted Traffic: It is crucial to identify