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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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observations and the current climate, so that we can describe the effects of climate change and the impact to the financial sector? Are you our new colleague? We are looking for a PhD candidate to develop AI
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challenging at temperatures approaching 20 K. Develop new methods to reveal how aerospace materials deform and become damaged under cryogenic and dynamic loading. Your research will contribute to safer hydrogen
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://www.academictransfer.com/en/jobs/363202/phd-candidate-development-of-hu… Requirements Additional Information Website for additional job details https://www.academictransfer.com/363202/ Work Location(s) Number of offers
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on the interpretation of research findings and their strategic and policy implications, supporting evidence-based decision-making and capacity building. Contribute to WSER's strategic development strengthening market
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our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors
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of electrocatalytic systems for H2O oxidation to H2O2, H2O reduction to H2 and NO3- reduction to NH3, in close connection to the catalyst development efforts in the consortium. Using operando XPS and soft XAS, you will
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erythrocytes, alongside biomarkers of inflammation and oxidative stress. Using combined laboratory and clinical data, empirically derived algorithms for subphenotype identification will be developed through
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of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from Mathematics (Inverse Problems), Computer Science (Machine
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of repeatedly solving wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim