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and waste heat sources will need to integrate multiple supply options with varying temperature levels. To support effective planning, energy professionals at the district and city level must be able
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work with rich datasets, advanced analytical tools, high-performance computing infrastructure, cutting-edge photonic sources, and modern industrial machinery. In this position, you will contribute
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Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early
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high-performance computers to better understand our planet and to address pressing environmental and societal challenges. The heart of ETH Swiss GeoLab will be a technological platform designed to
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the health and performance of humans in several situations (e.g. firefighters, who are exposed to extreme heat, or older adults who are exposed to heat stress during heat waves) by modeling the environment
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technologies promise to revolutionize multiple branches of science by solving problems that cannot be tackled by classical systems. While efficient and large-scale quantum computers are still far from being
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and interpretation of large-scale datasets, in particular next generation sequencing (NGS) data. The team covers raw data processing, high-performance computing, statistical evaluation, interpretation
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mutual learning. Access to high-performance computing. Terms of employment: The desired starting date is September 1st, 2025. We are looking for a postdoctoral researcher/senior scientist for an initial
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, continuous integration). Adapt software for parallel computing, optimization workflows, and high-performance computing environments. Contribute to software deployment, testing, and benchmarking across multiple
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elasticity, dissipation, and slender geometry interact to influence crack initiation and growth. Using in-house codes and high-performance computing resources, the candidate will simulate fracture processes