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) influence system performance and trade-offs. The research will combine analytical modelling with data-driven and AI-based methods, for example for scenario generation or uncertainty exploration. The PhD will
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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and uncertainty (e.g. demand evolution, renewable generation) influence system performance and trade-offs. The research will combine analytical modelling with data-driven and AI-based methods
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-based optimization, enabling autonomous measurement campaigns and real-time data assimilation. This research combines fluid mechanics, artificial intelligence, and robotics to establish the foundation
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15 Jan 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Mathematics » Statistics Researcher Profile First