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materials and energy-intensive manufacturing processes. These machines dominate current electric powertrain solutions but pose challenges in terms of resource supply chain, recyclability, and embedded carbon
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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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Supervisors: Dr Abhay Vincent This is a fully funded PhD (fees and bursary) in experimental icing research. Fundamental understanding of droplet impact dynamics is integral to icing. The overall aim
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PhD title: Mixed Methods Study of Depression Research Clinics as a means of addressing the primary-secondary care gap in NHS service provision. Principal supervisors: Dr Neil Nixon (School
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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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This is a fully funded PhD (fees and bursary) in experimental icing research. Fundamental understanding of droplet impact dynamics is integral to icing. The overall aim of this PhD is to use optical
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life
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the ability to use a microscope and work with scanned images are all desirable. Support: REP student will work closely with Julija Fediajevaite (PhD student) and members of the Soil Ecology Group. JF will
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This 4 year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will received an annual tax free stipend set at
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related PhD projects on behavioural change and weight loss. The successful doctoral candidate will lead a randomised controlled trial, including participant recruitment and coordination of laboratory