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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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bring interdisciplinary expertise on energy transitions, with a solid understanding of renewable energy integration, multi-energy systems, and energy conversion and storage technologies. You have strong
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understanding of district heating and cooling, renewable energy integration, multi-energy systems, and energy conversion and storage technologies. You have strong skills in programming, modelling, and data
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by multi-parameter sensing and creating digital twins of heat-sensitive biological systems (food, humans) that can live together with their real-world counterparts. This project aims to identify better
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in physics-based modeling at multiple scales. We bridge the virtual to the real world by multi-parameter sensing and creating digital twins of heat-sensitive biological systems (food, humans) that can
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by multi-parameter sensing and creating digital twins of heat-sensitive biological systems (food, humans) that can live together with their real-world counterparts. This project aims to better identify
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. Empa is a research institution of the ETH Domain. For a fundamental project, funded by the Swiss National Science Foundation (SNSF), we are looking for a highly motivated student with a strong background
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9 Oct 2025 Job Information Organisation/Company Empa Research Field Chemistry » Other Engineering » Materials engineering Engineering » Mechanical engineering Researcher Profile First Stage
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10 Oct 2025 Job Information Organisation/Company Empa Research Field Chemistry » Other Environmental science » Water science Physics » Chemical physics Researcher Profile First Stage Researcher (R1
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. Empa is a research institution of the ETH Domain. Empa’s Laboratory of Biomimetic Membranes and Textiles develops novel smart fibers, textiles and membranes for body monitoring, drug delivery and tissue