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to support a circular bioeconomy. We are seeking a highly motivated postdoctoral researcher to develop and apply machine‑learning and data‑science methods, with a focus on computer vision, to enhance wood
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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We look forward to receiving your online application including a: CV publication list statement of research interests and the names and contact information of at least two references. Please note
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100%, Zurich, fixed-term The Swiss Data Science Center (SDSC) and the WSL Institute for Snow and Avalanche Research (SLF) are seeking a PhD student for a Swiss National Science Foundation (SNSF
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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30 Jan 2026 Job Information Organisation/Company Paul Scherrer Institut Villigen Research Field Engineering » Mechanical engineering Engineering » Nuclear engineering Environmental science
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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23 Jan 2026 Job Information Organisation/Company ETH Zürich Research Field Computer science » Computer architecture Computer science » Programming Computer science » Other Engineering » Biomedical
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Ph.D. Position in Organic Chemistry, Polymer Chemistry, and/or Sol–Gel Chemistry & Materials Science
4 Feb 2026 Job Information Organisation/Company Empa Research Field Chemistry » Inorganic chemistry Chemistry » Other Engineering » Materials engineering Researcher Profile First Stage Researcher
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on our work and constantly improve it. We believe that the world can be improved with open data. Project background As part of our Open Science team, you will support us in developing efficient data