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. Candidates must possess or expect to obtain, a 2:1 or first-class degree in Engineering, Chemistry, or related physical sciences related discipline. To apply: send covering letter, CV and academic transcripts
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-hole-hunters.org) which permit the vast amount of optical survey data taken by instruments such as TESS to be studied, and self-lensing events searched for. The student will have an opportunity
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. Supervisors:Dr Isabella Guido and Dr Richard Sear Entry requirements Open to candidates who pay UK/home rate fees. See UKCISA for further information . Starting in January 2026. Later start dates may be possible
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
amounts of maintenance and operational data, from sensor streams to technical logs, yet much of it remains unstructured, fragmented, and underused. Hidden within these records are insights that could help
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information on the admissions process generally, please visit our How to Apply for a Research Degree webpage or contact the Doctoral College . Applications will not be considered if information is missing
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automated rankings. The research includes real-world validation using university admissions data and will contribute to the broader fields of AI in education and ethical decision-making. This PhD research
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programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full-time). More information on the department and the programme is available at the departmental prospectus page here: https://www.kcl.ac.uk
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atomisers. To ensure high quality measurement data, enabling meaningful correlations, measurements will be performed on a simplified prefilming geometry, with aero and hydrodynamic features representative
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Fully funded positions available to start in 2025 or early 2026 Projects span plant genetics, climate-resilient breeding, AI and data science, soil health, sustainable agriculture, circular economy