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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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Start date: November 2025 This PhD is an exciting opportunity to expand knowledge and understanding in the applications of natural chitinous polymers for bacterial/viral prevention and biofilm
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
system health monitoring, and more efficient maintenance planning. Digital twins offer a powerful foundation but must evolve beyond simulation to truly support engineering decisions. This PhD will develop
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by
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PhD Studentship Aircraft Electrical Power System Stability This exciting opportunity is based within the Power Electronics and Machines Centre (PEMC) Research Group at Faculty of Engineering which
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in collaboration with industry leaders
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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/emissions modelling preferred but not required Creative problem-solving skills and ability to work independently *Candidates with a PhD in other disciplines may be eligible if they can demonstrate exceptional
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project