179 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at ETH Zurich
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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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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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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
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Researcher or experienced Data Scientist to harness AI, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental
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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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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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, 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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well as the accomplished research project BOTTOMS-UP. Depending on your skills and preferences, Artificial Intelligence (Machine Learning) can be used for predicting aspects of forest biodiversity based on existing as