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Tomography (XCT), a non-destructive imaging technique, to perform crushing experiments of TRISO particles over a range of temperatures, thereby achieving a better understanding of the deformation behaviour
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defects without compromising structural integrity, thus ensuring passenger safety and operational efficiency. The project aims to design and prototype a ground-based automated inspection system capable
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per year for 3.5 years. Lead Supervisor’s full name & email address Dr Massimiliano Fasi: m.fasi@leeds.ac.uk Project summary The growing importance of artificial intelligence is fostering a paradigm
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adaptive signal processing whose combined performance and resilience can easily exceed that of the sum of their parts. However, fundamental and significant questions to provide their practical feasibility
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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of the underlying the physical processes leading to predictability and forecast skill of North Atlantic cyclones. The project will also explore statistical post-processing methods to see if raw forecast skill can be
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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PhD Studentship: Towards Sustainable Powertrains: Enabling High Motor Performance without Rare Earth Materials and Energy intensive Manufacturing Processes The University of Nottingham This project
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imaging using 3 Tesla MRI scanning to investigate brain biomarkers. Collaborate with clinical experts and patient groups, attend conferences and meet leading research experts. Project aims and objectives
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outputs for publication in medical journals. Master cutting-edge laboratory assessments of health and imaging using 3 Tesla MRI scanning to investigate skeletal muscle and energy metabolism biomarkers