228 computer-science-intern "https:" "https:" "https:" "https:" "U.S" "U.S" uni jobs at ETH Zurich in Switzerland
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100%, Zurich, fixed-term The ETH Zurich Geothermal Energy & Geofluids (GEG.ethz.ch) Group in the Department of Earth and Planetary Sciences investigates subsurface reactive fluid and geothermal
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demonstrate outstanding research and teaching records and a proven ability to direct research work of high quality. We welcome candidates from all areas of Statistics and Data Science, broadly defined. The new
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environment where philosophy meets data science, public health, medicine, and law? At the Health Ethics & Policy Lab (https://bioethics.ethz.ch ), you will join a team committed to shaping responsible
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environment spanning real-time graphics, large language models, and affective computing Regular 1-on-1 mentoring and weekly team meetings Collaborative, international team at ETH Zurich's Computer Graphics
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100%, Zurich, fixed-term ETH Zurich is one of the world-leading universities for science and technology. At ETH Zurich, researchers experience a climate which inspires top performance. Situated in
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backgrounds including biology, medicine, psychology, biochemistry, physics, engineering, computer science, and economics investigate fundamental questions about how the brain functions in health and disease
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and professionals across emerging areas like machine learning, cyber security, climate risk, distributed ledger technology, and quantum computing and translates that expertise into integrative research
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of methods to program material stiffness in-situ with light. Goals: high stiffness contrast (rigid-soft), fast transition (<1s), and small form factor (< mm scale) Characterization and developing theoretical
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climate change at one of the leading international universities for natural sciences and technology chevron_right Working, teaching and research at ETH Zurich We value diversity and sustainability In line
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100%, Locarno, fixed-term Recent advances in AI-based weather prediction have demonstrated remarkable skill and computational efficiency. However, most current machine-learning weather prediction