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    Seed Projects 2023
    Title Contact Math Contact SEE
    Faster AtmoSpheric Transport modeling using Dimensionality REduction and Acceleration of with Machine learning (FAST-DREAM)

    Charlotte Debus and Martin Frank

    Hoshyaripour Ali and Corinna Hoose

    Exploring the Potential of machine learning methods for improving operational hydrological forecasting and prediction (EPOforHydro)

    Sebastian Krumscheid

    Uwe Ehret

    RoughFlow: From roughness to fluid flow in natural fractures and faults

    Steffen Winter

    Philipp Blum

    Multilevel Methods for Quality Assessment of Injection Molding under Uncertainty

    Sebastian Krumscheid

    Florian Wittemann, Luise Kärger

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