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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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system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical, spatial, and infrastructural constraints. The work aims to identify
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approaches. The PhD will develop and apply optimization-based energy system models to analyse whether spatially coherent urban and energy configurations can be operated efficiently under realistic physical
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14 Mar 2026 Job Information Organisation/Company Empa Research Field Chemistry » Analytical chemistry Chemistry » Biochemistry Chemistry » Computational chemistry Chemistry » Inorganic chemistry
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. Empa is a research institution of the ETH Domain. The Coating Technologies Group in Empa's Laboratory for Surface Science & Coating Technologies performs physical vapor deposition (PVD) of innovative
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of electron spectroscopy experiments Modelling of experimental data Your profile The position is immediately available for a candidate with a master's degree (or equivalent) preferably in physics, physical
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We are looking for a motivated PhD student to explore the muon spin spectroscopy for perovskite solar cells research. This position is part of Muoniverse, a Swiss National Centre of Competence in
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. Empa is a research institution of the ETH Domain. We offer an opportunity to join an exciting project within the Laboratory for Air Pollution / Environmental Technology at Empa, in collaboration with ETH
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. Empa is a research institution of the ETH Domain. Within our focus research Digital Health Solutions, we develop technologies for continuous long-term monitoring of individuals. At the Biomimetic
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. Empa is a research institution of the ETH Domain. Your tasks Amorphous materials play a key role in sustainable catalysis and energy conversion, but their disordered atomic structure makes them difficult