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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a
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to water, with the Zinc acting as the anode and hydrogen evolution potentially occurring at the steel surface. The successful PhD candidate will work at the forefront of hydrogen materials research, with
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This PhD project offers the opportunity to explore a rich and rapidly developing area of research where powerful mathematical ideas unlock exact solutions in quantum physics. Most physical systems
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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will be defined, decomposed and assessed through attention to artefacts and practices across a range of sectors and disciplines. Focusing on the automotive context, the project will develop a
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to apply early. The second quantum revolution aims to create devices that exhibit a quantum advantage – a step-change in performance gained by leveraging properties of quantum mechanics. The development
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This PhD project will develop next-generation grid-scale energy storage solutions integrated into HVDC (High Voltage Direct Current) systems at the University of Edinburgh, in partnership with UK
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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NO2 causes an increase in O3. Statistical methodological developments are required to understand the relationship between air pollutants and health outcomes to account for both the size and nature
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of our approach is the innovation of novel methods to investigate genome function. For example, we have recently developed ways to map the binding of nucleic acid-interacting drugs and small molecules