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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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that explicitly incorporates protein–ligand dynamics. You will be responsible for: Designing and implementing innovative deep neural network models. Integrating physical principles and molecular modeling knowledge
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cooling, convective exchange with the environment, biochemical quality attribute evolution within the products, and thermally-driven damage (chilling-freezing injury). Use these models to build physics
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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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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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10 Nov 2025 Job Information Organisation/Company ETH Zurich Department Institute for Building Materials Research Field Engineering » Biomaterial engineering Engineering » Materials engineering
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24 Oct 2025 Job Information Organisation/Company ETH Zürich Research Field Computer science » Other Mathematics » Applied mathematics Physics » Computational physics Physics » Quantum mechanics
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9 Oct 2025 Job Information Organisation/Company ETH Zürich Research Field Chemistry » Other Physics » Condensed matter properties Physics » Optics Physics » Other Researcher Profile First Stage
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27 Sep 2025 Job Information Organisation/Company ETH Zürich Research Field Engineering » Other Physics » Condensed matter properties Physics » Optics Physics » Quantum mechanics Researcher Profile
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Description Two PhD positions in atmospheric selenium research: field & lab analyses and process-based modeling We are seeking two highly motivated and curious PhD students to join the Inorganic Environmental