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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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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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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
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might include flow diagrams, use cases, electronics block diagrams, the high-level layout of component arrangements or source code. Supervisory Team: The candidate will be supervised within
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@bristol.ac.uk ) 4th Supervisor: Professor Jenni Barclay (J.barclay@bristol.ac.uk ) Applications are invited for a fully funded three years PhD studentship. The studentship will start on 1st January 2026
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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
investigate the large area production of graphene, BN, MoS2 and other layered materials, optimize their transfer process in view of their application in energy, electronics and photonics. This will include
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative