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(https://www.unibas.ch/en/Research/Values-Ethics/Diversity-and-Inclusion.html ), we are committed to sustain and promote an inclusive culture, ensure equal opportunities and value diversity and respect in
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dynamics simulations is highly desirable. Basic knowledge of machine learning is considered an advantage but is not mandatory. LanguagesENGLISHLevelExcellent Additional Information Work Location(s) Number
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to staff position within a Research Infrastructure? No Offer Description PhD Position in Physics-Informed Machine Learning for Cardiac Magnetic Resonance The CMR Zurich group at the Institute
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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systems, and space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where
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combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
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with competitive salary according to ETH standards Interdisciplinary and international research environment You can expect numerous benefits , such as public transport season tickets and car sharing, a
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energy transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal
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computational analyses of single-cell, spatial transcriptomics, and multi-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI
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stable water isotope data, and Statistical analyses, including machine learning approaches. The full-time position is funded for four years. Salary and social benefits are provided according to ETH Zurich