445 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Switzerland
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application form. https://apply.refline.ch/673277/1335/index.html?lang=en Company Eawag, the Swiss Federal Institute of Aquatic Science and Technology, is an internationally networked aquatic research institute
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Engineering » Computer engineering Engineering » Control engineering Engineering » Electrical engineering Engineering » Industrial engineering Engineering » Materials engineering Engineering » Mechanical
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technology development. The lab combines cutting-edge methods such as functional two-photon microscopy, high-density neuropixels electrophysiology and spatial biology research, alongside computational analyses
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cellular biology. The position is available from 1 February 2026. The initial contract will be for one year. For more information on research in the Hondele lab see: https://www.biozentrum.unibas.ch/research
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, advanced high-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative
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-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative disciplines
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on ultrafast quantum dynamics in condensed matter. The candidate will acquire expertise at the frontiers of ultrafast science and apply it to conduct cutting-edge research on quantum materials. Further project
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. Publications in major international peer-reviewed journals. START DATE: October 1st, 2026 or upon agreement Mandatory online registration before February 6th 2026 at: http://www.unige.ch/academ Further enquiries
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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expertise in cell culture and mouse studies. As the work involves the analysis of spatial transcriptomic data, basic expertise in computational biology, with experience in R and/or Python will be beneficial