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operationalization in the MeteoSwiss environment and support of developed methods Analysis of results and their communication for different user groups Support users with optimal usage and interpretation of scenario
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automation to enable closed-loop, self-optimizing experiments Initial experiments will investigate phase equilibria and transport processes in liquid mixtures The work will be conducted in tight integration
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, selecting the approaches best suited to the project's requirements You will integrate the resulting sensors into one of the lab's existing tendon-driven robotic hand platforms, optimizing readout electronics
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15 Jul 2026 Job Information Organisation/Company ETH Zürich Research Field Engineering » Electrical engineering Engineering » Systems engineering Physics » Computational physics Physics
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habitual control. It will then test how acute stress alters these processes, combining behavioral performance, physiological monitoring, movement-based phenotyping, and advanced statistical and computational
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of results and their communication for different user groups Support users with optimal usage and interpretation of scenario products Profile MSc in natural science or computational science and preferably a
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and institutions that interact with them. You should bring: A master’s degree in computer science, machine learning, HCI, or a related field. Strong foundations in machine learning and familiarity with
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-prevention antibody/nanobody program from discovery toward the clinic (start immediately or by arrangement). Your path: from fellowship to founding Over the 12 months you will drive the antibody program toward
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24 Jun 2026 Job Information Organisation/Company ETH Zürich Research Field Biological sciences » Other Computer science » Other Medical sciences » Other Researcher Profile Recognised Researcher (R2
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. Depending on experience and interests, the project may include: Development of next-generation focused ultrasound systems fMRI-guided treatment planning and targeting Optimization of targeted drug delivery