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different methods such as modeling mass flows analysis (MFA), Life cycle analysis (LCA) and semi-quantitative methods for decision support for sustainable innovation. PhD Student in Safe and Sustainable Green
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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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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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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