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100%, Zurich, fixed-term We have an open PhD position at the intersection of machine learning, embedded intelligence and human–computer interaction. The project will explore how learning systems can
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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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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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machine learning models, and develop a generalizable decision-support system for vehicle and station allocations. This research will be conducted together with domain experts and collaborators. The research
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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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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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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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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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tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH Zurich We value diversity and