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collaboration to combine their expertise. By integrating these complementary approaches, we aim to provide the first comprehensive picture of Hsp90's structure–dynamics–function relationship, with broad
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of nanoparticles for healthcare and industrial applications. As a PhD candidate, you will: Develop and refine SAXS and FCCS methods to quantify size, concentration, density and internal structure of diverse
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of IAI mechanisms and develop innovative antibacterial biomaterials to improve patient outcomes. Structured around three core scientific pillars—regenerative medicine, biomaterial science, and
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structure-performance relationships for catalysts for the hydrogenation of CO2 to higher alcohols (such as ethanol). The role of this specific PhD position will be the development of model catalysts and their
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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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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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, 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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established research group at the University of Zürich, focusing on the structural effects of posttranslational modifications within intrinsically disordered proteins. Our work combines biomolecular NMR with
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protein-DNA interactions) Produce stable complexes between proteins and/or DNA Determine structures of proteins/complexes Design mutants and perturbations for in vivo experiments Perform in vivo functional