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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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. Empa is a research institution of the ETH Domain. The Laboratory Chemical Energy Carriers and Vehicle Systems Laboratory conducts, develops and optimizes processes for renewable fuels. The group
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, antibiotic resistance genes, VOCs and PFAs. Investigations on electrode materials, manufacturing processes, signal amplification and modulation are underway. We strive to strengthen environmental applications
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related field. You bring a strong analytical background and are proficient in areas like geometric deep learning, signal processing, statistics, or learning theory. Knowledge of energy systems, multi-energy
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written and spoken. Experience with experimental fluid mechanics and computer vision is an advantage. Our offer We offer a stimulating, multidisciplinary research environment within the ETH Domain, with