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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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) 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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chemistry or materials science. Experience in surface science and hydrogen technology is of advantage. The ideal candidate has an independent, target- and solution-driven work attitude, inter- and
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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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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15 Jan 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Mathematics » Statistics Researcher Profile First
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plumes from point sources using the MicroHH atmospheric model. Analysis of plume dynamics and NOx chemistry in the high-resolution simulations. Develop and refine data-driven methods for emission