223 systems-science "https:" "https:" "https:" "https:" "UNIV" uni jobs at ETH Zurich in Switzerland
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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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at adam.altenhof@eaps.ethz.ch and/or Dr. Xiang-Zhao Kong at xkong@ethz.ch . About ETH Zürich ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our
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. Joël Mesot. The closing date for applications is 22 February 2026. We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://ethz.ch/en/the-eth-zurich/working
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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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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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80%-100%, Zurich, fixed-term The Swiss Data Science Center (SDSC) is a national research infrastructure in data science and artificial intelligence (AI) of the ETH domain, with EPFL and ETH Zurich
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screening platforms, with a focus on skin tissue models, including fibrosis. We are embedded within the Tibbitt group, in the Macromolecular Engineering Laboratory . Project background The glycocalyx is a
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interpretation of explosion events in underground ammunition storage facilities. The position is embedded in a collaborative project with armasuisse Science and Technology and partners from industry and the Swiss
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100%, Zurich, fixed-term The Advanced Manufacturing Lab (am|z) at the Department of Mechanical & Process Engineering (D-MAVT) at ETH Zurich develops advanced manufacturing methods and systems
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-scale geospatial and Earth system datasets, within the NCCR CLIM+ program. The role bridges climate science and AI, developing novel methods for climate data analysis, downscaling, and synthesis using