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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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Chemistry » Molecular chemistry Chemistry » Inorganic chemistry Chemistry » Physical chemistry Chemistry » Other Engineering » Materials engineering Physics » Acoustics Physics » Applied physics Physics
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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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for PhD students and postdocs. Learn more at https://www.muoniverse.ch/ . Muoniverse positions often serve as bridges between individual research groups and institutions, supported through dedicated
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required. Our offer We offer this postdoc position at a research institution with excellent infrastructure and broad interdisciplinary surrounding. Position starting from June 2026 or upon agreement. We live
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keen interest for bio-imaging. Completed Master`s degree in molecular/structural biology or biophysics. An outstanding academic record. Previous experience in protein imaging using atomic force
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of measurement systems, signal processing and analysis and the assessment of measurement accuracy, robustness and long-term stability. The resulting data form the basis for model-based approaches to evaluating
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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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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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activation and micromechanical modeling Progressive damage modeling of reinforced FRPs Mechanical characterization and fracture experiments Complete a PhD thesis at ETHZ Your profile Highly motivated and