178 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at ETH Zurich
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, leveraging advanced machine learning to combine these diverse data sources. By identifying the most informative clinical features, the approach seeks to provide more accurate and interpretable recovery
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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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methods in learning sciences and educational research You are preferably studying Computer Science or a related field You are interested in Learning Sciences or Human-Computer Interaction (HCI) You are
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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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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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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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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