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is to place the UFTEs in the market as an advanced research tool. Job description Soldering electrical components and UFTEs to printed circuit boards 3D-printing, machining and electrochemical
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COMPAS XR framework developed at ETH Zürich. Project background The successful candidate will work at the intersection of computational design, XR, human-computer interaction, and robotic fabrication, with
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dynamics simulations is highly desirable. Basic knowledge of machine learning is considered an advantage but is not mandatory. LanguagesENGLISHLevelExcellent Additional Information Work Location(s) Number
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not only supports your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a
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to positive change in society We are actively committed to a sustainable and climate-neutral university You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range
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season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits Working, teaching and research at ETH Zurich We value diversity and sustainabilityIn
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forces and stress fields in such systems Develop and use machine-learning based models to correlate particle deformation and contact forces in 3D systems Profile Applicants for this PhD position
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who share our guiding principles: Curiosity: You enjoy learning, exploring new ideas, and understanding problems deeply. Openness: You listen, collaborate, and are receptive to different perspectives
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qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and
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benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH