185 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"U.S" positions at ETH Zurich
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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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with the ability to work across multiple projects in a collaborative academic environment. We are looking for someone with: Master’s degree in aerospace engineering, electrical engineering, computer
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fields, and Gaussian Splatting). Profile Degree in Computer Science or a related field, with several years of professional experience as a software engineer Strong proficiency in Python and C#, and
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results effectively within the lab and to broader scientific audience Profile Education & Experience: Master’s degree required; PhD preferred in Computational Biology, Bioinformatics, Data Science, Computer Science
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for open-ended arrangement. Workplace: ETH Zurich, with close interaction across departments and partner institutions worldwide. Further information about Professorship for International Relations and Data
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, workshops, and events is also part of your responsibilities, as is serving as an interface between research and administration. Profile Completed university degree (PhD) in mathematics, computer science
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establish and develop a centralized pool of space specialists. This resource pool will bolster ETH Zurich-led space projects, positioning ETH Zurich as a key player in both the national and international
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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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reproducible workflows Coordinate development priorities and contribute to reporting and planning within the Forest Studio team Collaborate with interdisciplinary teams and contribute to international research
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Digital Twins for Human Learning. Project background In cognitive science, it is common practice to use cognitive models to understand human thought processes – including human learning. Large language