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, dynamical systems and statistical physics. The candidate will be jointly supervised by the Coventry team Dr Fei He and the Stellenbosch team Prof. Francesco Petruccione . This project will contribute
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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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). Supervisors Primary supervisor: Prof. G.Tasca. Co-supervisors: Prof. J.Diaz-Manera, Dr. S.Cockell. Eligibility Criteria You must have, or expect to achieve, at least a 2:1 Honours degree or international
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related discipline. To apply, please contact the supervisor, Prof Foster - david.foster@manchester.ac.uk . Please include details of your current level of study, academic background and any relevant
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for greater precision. Machine learning (ML) algorithms will analyse these datasets to deliver a scalable, cost-effective system, validated through field trials and enhanced by contributions from four
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Supervisory Team: Prof Middleton, Prof Gandhi PhD Supervisor: Matt Middleton Project description: We know of only 20 or so black holes in our galaxy yet predict there should be 10s of millions
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of this project, please contact Prof. Tony McNally (T.McNally@warwick.ac.uk ) directly for further information. Essential and Desirable Criteria: 1 or 2.1 degree in Materials Science & Engineering, Chemical
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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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to the Centre. Warwick Manufacturing Group Three successful offer holders will be under the supervision of Prof. Louis Piper and Dr. Mel Loveridge in the Warwick Manufacturing Group. Prof Piper and Dr Loveridge
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structures. Accurate detection and quantification are therefore essential for quality assurance and structural integrity assessment. This project, supervised by Dr. Leandro Maio and Prof. Prasad Potluri, will