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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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trials with prototype vehicles and human drivers. The position will include some travel to project partners and test tracks. Who we are looking for: To qualify as a PhD student, you must have a Master's
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the field.Vacancy 1: PhD (4 years) on experimental and numerical characterization of composites processing for hydrogen tanks[Net salary (after taxes) starting from 2600 EUR/month]Belgium has been taking a leading
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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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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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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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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 19 days ago
of critical thinking Experience with photonics, fluorescence, imaging or biochemical methods is helpful Our offer Highly motivated team Flexible working hours World-class institute with outstanding
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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