177 machine-learning-"https:"-"https:"-"https:"-"Simons-Foundation"-"Simons-Foundation" positions at ETH Zurich
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background in AI/ML and experience with Python-based machine learning frameworks. A solid understanding of Linux systems and containerized deployment within Kubernetes is a strong asset. The candidate should
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(preferably Python), multiple years of programming experience as well as profound knowledge of professional computer-aided design and 3D modelling In addition, you have experience in CAD/CAM (preferably McNeel
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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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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 at process scales, the project combines efficient mathematical concepts like automatic differentiation with backpropagation – the same concept that powers machine learning and artificial
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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