345 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions in Switzerland
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- ETH Zurich
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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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Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or Master’s degree in Medicine (MD) with strong Python skills and some ML
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. Attractive employment conditions: Numerous benefits, e.g. public transport subscriptions and car sharing Childcare options Attractive pension benefits chevron_right Working, teaching and research at ETH Zurich
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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
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. The combination of biological and technological aspects is central in our group and in this project. A possible candidate should have strong disposition to learn and improve novel methods, should be very open to
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candidate should have strong disposition to learn and improve novel methods, should be very open to different research disciplines and should be able to communicate across disciplines. Good communication (in
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contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive
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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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upcoming areas off the beaten paths. Our three main areas of research are machine learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects
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our neural implant technology market-ready for commercialization The full lifecycle where you don't just design and build devices, but you also get to see them in action with in vivo brain-machine