227 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Chester" positions in Switzerland
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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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thermoplastic feedstocks for FDM printing Programming of an existing hybrid FDM printing machine, including printing and milling devices Modelling and optimization of the debinding process Simulation-based design
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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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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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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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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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scientist holding a PhD in physics or astronomy, with a strong background in software development and machine-learning applications, demonstrated through contributions to open source projects and production
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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