408 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" positions in Switzerland
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Laboratory is located in St. Gallen at the Swiss Federal Laboratories for Materials Science and Technology (Empa). Our team is highly interdisciplinary and international, providing an inspiring environment
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and networking platform to support the development and application of Earth system, weather, and climate modeling, data infrastructure, and impact research. Project background There is an ever
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AXA Post-Doctoral Fellowships aim at supporting promising researchers on a topic aligned with AXA’s priorities and societal challenges. For detailed information about funding scheme, specific topics
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100%, Zurich, fixed-term We invite applications for a PhD position on Data-driven and hybrid hydrological modeling co-supervised by Manuela Brunner (ETH Zurich, WSL) and Olivia Martius (University
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of emerging technologies balanced against their dark sides. Our research at the intersection of data, behavioural, and computer science draws on data from real-world and experimental settings The Centre for AI
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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psychologists, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU
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intelligent materials. Our work explores new paradigms for monitoring infrastructure through physics-based modeling, sensing systems, and data-driven approaches. The advertised position is part of a research
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Scientist. Your position Enabling research projects by developing and deploying IT solutions tailored to chemical research workflows. Advising and supporting researchers on research data management
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the approach of Large Language models, the aim of the WeatherGenerator is to build a so-called foundation model for Weather and Climate. The model will be trained on various model data as well as many