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CoSi project (Co-Evolution and Coordinated Simulation of the Swiss Energy System and Swiss Society), we are seeking a motivated and qualified PhD candidate to develop neighbourhood- and district-scale
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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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. 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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layers, thorough FLA processing, and extensive materials characteri-zation using XRD, electron microscopies, TOF-SIMS, electrochemical methods, etc. Modeling and simulations should help us to explain
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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. 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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their subsequent simultaneous analysis. This project aims at overcoming these challenges to reliably measure atmospheric levels of PFASs and model their respective emission strengths in Switzerland
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nanoparticle systems. Investigate model particles such as liposomes, mesoporous silica and silver nanoparticles. Investigate RNA-LNP formulations for next-generation gene therapeutics, examining how lipid
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, Electron Microscopy, and Numerical Simulations. Your research will contribute to the development of innovative metamaterials with hydrogel-ceramic nanocomposites base materials that feature tunable
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details of two reference persons. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa