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sensors to understand their local surroundings at sea and inform optimal action. To ensure safety requires the ability to reliably detect, image and recognise their environment, in terms of surrounding sea
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Applied mathematics, fluid mechanics, high-performance computer simulations. Full time, fixed term position (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship Higher
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15.04.2025, Wissenschaftliches Personal The Lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is inviting applications for a fully funded PhD position in interpretable machine
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their evolution during catalytic operation and activation. You will apply advanced electron diffraction techniques (3DED, 4D-STEM tomography), atomic resolution STEM imaging (HAADF, ABF), EDX and EELS
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single industrial environmental burden of our generation. Disruptive innovations are required for alternative reduction processes that convert mineral ores into metals without today’s carbon-based methods
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We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only
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Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of
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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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we don’t know how interaction with others changes our own metacognitive states of mind, and how these mental processes can vary and go awry. This project aims to find out how social communication
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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