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processes as droplets/condensates wet membrane compartments in cells. Numerical simulations and theoretical membrane models will be developed, aiming to couple viscous interfacial fluid flow, elastic
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues for understanding solid earth and cryosphere dynamics, and their
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of three topics: 1. Combining synthetic aperture radar (SAR) images with probabilistic weather prediction models to view and predict dynamic sea ice properties. 2. Using multi-frequency SAR, coupled with in
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is experimental and will be conducted in our lab facilities, also incorporating theoretical models of complex flow. Fieldwork is planned in collaboration with a non-profit organization in Morocco
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. Experimental work could include the design, construction, and testing of prototype storage systems, while simulation efforts may focus on thermal modelling, system optimization, and safety analysis
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. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining
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well as of the cyclone family itself. The candidate will investigate the mechanisms by which moisture is drawn into and processed within cyclone families using reanalyses, idealised and realistic model simulations
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of the art in mathematical and numerical modelling of CO2 storage? This might be the right position for you! About the project/work tasks: About the project TIME4CO2 TIME4CO2 aims at advancing simulation
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updates, and interoperability at scale. In close collaboration with project partners, the PhD candidate will focus on relevant data modeling and processing approaches for data gap filling, redundancy