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applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be carried out in close collaboration with our interdisciplinary teams at both Empa and EPFL, as
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, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting
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