139 computer-programmer-"https:"-"CEA-Saclay" "https:" "https:" "https:" "https:" "Inserm" positions at ETH Zurich
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that are transferable to a broader landscape of opportunities. You will have the opportunity to visit industry and other academic institutions within the consortium. After completing the program, you will have a thorough
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policy, political economy, economics, sociology, computational social sciences, or a related field Strong knowledge of advanced quantitative methods is essential (e.g., econometrics, causal inference
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software for scientific data analysis. B: A computer scientist or software engineer specialised in algorithmic optimisation and data structures, with demonstrated accomplishments in the context
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the Science in Perspective Program . Contribute to interdisciplinary research and teaching initiatives in partnership with computer science faculty, researchers, and students at ETH Zürich. Engage on topics
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is to build efficient and robust computational tools for analyzing complex engineering systems. Applications include structural dynamics and other dynamical systems relevant to real-world engineering
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have enabled unprecedented control over light-matter interactions, catalyzing breakthroughs in imaging, nonlinear optics, and photonic computing. We leverage these developments to advance the field
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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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using emerging non-invasive exhalomics (exhaled breath metabolomics) approach. The research program integrates animal experiments with advanced analytical techniques and bioinformatics to enhance
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100%, Basel, fixed-term The Computational Evolution Group, led by Prof. Dr. Tanja Stadler, in the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zürich works at the interface
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. Neuromorphic computing and ML deployment on digital and neuromorphic processors TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems Techniques such as quantization, pruning