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Field
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that generalize across different physical settings. Building on this motivation, the project focuses on the definition, development, and analysis of scientific foundation models: large-scale, generalizable models
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. Consequently, the candidate must demonstrate skills and a strong interest in these two disciplines. Additionally, the candidate must show an aptitude for data processing and numerical simulation. Proficiency in
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of flexible hydropower operation on potential internal erosion processes in embankment dams. The research will involve experimental investigations, data analysis, and possible field work, in collaboration with
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staff of around 120, including 66 permanent staff. It has a strong experimental component, with numerous prototype set-ups supported by both standard equipment and high-tech instrumentation
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Build, Division of Civil and Environmental Engineering, within the general study programme Civil Engineering and work with numerical modelling, time series analysis, and soil characterization
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skills (e.g., numerical methods, statistical analysis, coding, data management) Good communication skills Ability to work in a team Driving license category B desirable (access to field sites) Your Tasks
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, from fundamental theory, laboratory experiments, and detailed numerical simulations, to mesoscale pore network modeling and upscaling to continuum-scale theories that can be applied in application
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activity of individual neurons and mesoscopic population signals. His team develops open software for analysis and data management that forms the technical basis of the proposed project. The PhD candidate
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of surface water, groundwater, and probabilistic seepage analysis, together with modelling and uncertainty assessment techniques. Consideration of these interacting processes may help improve the accuracy and
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benchmarking and performance analysis against state-of-the-art studies Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate experimental systems