232 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" uni jobs in Switzerland
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work on designing novel Smart Sensors & Energy Efficient Machine Learning on Microcontrollers. The objectives of this thesis include: Design and prototype modular, low-cost sensor nodes integrating
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knowledge and technology from research to Swiss machine, electrical and metal industries. The research group additive manufacturing at inspire offers in collaboration with the Advanced Manufacturing Lab (amlz
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CAD packages (Autodesk Revit, Archicad and cadwork3d) and work in a multi-disciplinary team of software engineers, architects, computer scientists Your projects will include multi-disciplinary
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commitment to documentation of experimental work. • Ability to work independently within a collaborative research team. • Motivation to learn new techniques and contribute to interdisciplinary research
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100%, Zurich, fixed-term The Professorship for Research on Learning and Instruction at ETH Zurich strives to discover effective, evidence-based ways to improve educational practice with an eye
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learned perception can drive action in a closed loop and how we can leverage foundation models for long-term autonomy. To this end, we are looking for a capable lab technician / engineer who supports our
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incl. purchasing, stocking, monitoring Management and maintenance of basic lab equipment and machines incl. regular checking, organization of repair with institute infrastructure personnel, planning
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, students gain valuable hands-on experience and learn essential skills for their future. That’s why we’ve created an ecosystem where students - Bachelor’s, Master’s, and Doctoral - are encouraged to ideate
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, students gain valuable hands-on experience and learn essential skills for their future. That’s why we’ve created an ecosystem where students - Bachelor’s, Master’s, and Doctoral - are encouraged to ideate
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postdoctoral researcher in Robot Learning who is interested in questions such as: How can we fuse representations of the world with modern learning-based methods to allow for larger scale / longer horizon? How