184 machine-learning-"https:"-"https:"-"https:"-"https:" positions at ETH Zurich in Switzerland
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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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. 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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, 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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models incorporating machine learning and modeling. Transcriptome recording and cellular history reconstruction We are advancing our CRISPR-based transcriptional recording method (Schmidt, Nature, 2018
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experimental and simulated data, leveraging AI and machine learning techniques Contribute to novel computational optimisation methods for machining processes Develop and implement automation solutions, including
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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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the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen), the SDSC provides
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tracking of minimally invasive robotic systems Autonomous control in uncertain anatomical environments Computer vision for image-guided robotic procedures (incl. endoscopic, MR-, US-guided) Surgical training