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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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Overview This research assistant post will enable the candidate to undertake a PhD on the diagnosis of pancreatic cancer, specifically focusing on examining the use of imaging before a diagnosis is
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves
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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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. cell culture, molecular biology, imaging, cell signalling assays). As well as performing experiments on the project, the role will involve providing training in techniques to relevant staff/students
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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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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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, 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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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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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You