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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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. Empa is a research institution of the ETH Domain. At Empa’s Centre for X-ray Analytics, we investigate bio-nano assemblies from lipid nanoparticles (LNPs) to polymer-based nanosystems using powerful
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xenon flash lamp. Over the last years, we have successfully applied FLA to crystallize thin films of TCOs (In2O3, In-Zn-Ga-O), refractory ceramics (Al2O3), and Li-based cathodes (LCO, LMO). Within
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anthropology and social science to biostatistics and mathematical modelling as well as observational cohorts with biobanks. The Environmental Exposures and Health Unit (EEH) of EPH is focused on research related
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world
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, for advancing our fluorescence-based DyeCycling/FRET technology to study biomolecular dynamics. Biomolecular dynamics, such as conformational changes, are the understudied link between biomolecular structure and
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near-instantaneous proliferation of comb lines and new regimes of spectral control. Project background This project will combine advanced numerical modeling with laboratory demonstrations to explore
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project (Decarbonization of Heating and Cooling), we are seeking a motivated and qualified PhD candidate to design integrated district heating and cooling systems. Future thermal networks based on renewable
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scanning probe instrumentation fabrication of van der Waals heterostructures transport, optical spectroscopy, and quantum sensing experiments data analysis, modeling, and scientific communication