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floods—in mountain catchments. The goal is to understand long-term changes in runoff regimes and flood hazards by combining climate-driven (glacier-)hydrological modelling with reconstructions of past
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will contribute to developing knowledge-driven decision-making models. The postdoctoral research fellow will actively participate during the supervision process of PhD-students as main or co-supervisor
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techniques such as signal processing and dynamic systems modeling, and will contribute to developing knowledge-driven decision-making models. The postdoctoral research fellow will actively participate during
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1st September 2025 Languages English English English The Faculty of Technology, Natural Sciences and Maritime Sciences have a vacancy for a position as PhD Research Fellow in Pioneering AI and
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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technological progress in our increasingly digital, data-driven world. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By
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networks in order to enhance fog net technology. The planned work is experimental and will be conducted in our lab facilities, also incorporating theoretical models of complex flow. Fieldwork is planned in
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Sufficient Statistics” . This position is placed at Integreat - Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway. Researchers at
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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 domainspecific knowledge with data
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