225 computer-science-intern-"https:"-"https:"-"https:"-"CUBO" positions at ETH Zurich
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cumulative PhD at the intersection of law, computer science, and empirical social science Our offices are located in downtown Zurich, and the working languages are German and English Profile We are looking
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of Bern). The position will be hosted at the Institute for Atmospheric and Climate Science at ETH Zurich and will be part of the NCCR CLIM+ programme which is funded by the Swiss National Science
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or mechanical engineering, or CS Solid knowledge of computer vision and ML, particularly anomaly detection methods Experience with multimodal data (e.g., image + time series, sensor fusion) is a strong ad-vantage
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Required Experience: PhD in Geodesy, Geomatics, Aerospace Engineering, Signal Processing, or a related field Proven experience in GNSS data analysis and processing Very good programming skills (e.g., Python
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collaboration with various stakeholders (engineering companies, Swiss Armed Forces, armasuisse, international collaborators) to ensure efficient roll-out of the system Profile MSc degree in Geophysics, Seismology
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The current era of artificial intelligence is predominantly driven by advances in computational power and infrastructure. As models scale to unprecedented sizes, their capabilities are enhanced
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development. Job description We are searching for a scientific assistant who assists and coordinates teaching activities in the international master program Spatial Development and Infrastructure Systems
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, Computer Science, Applied Mathematics, or a field focused on the intersection of Machine Learning and Optimization Proven expertise in surrogate modelling, specifically in designing neural architectures
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of emerging technologies balanced against their dark sides. Our research at the intersection of data, behavioural, and computer science draws on data from real-world and experimental settings The Centre for AI
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convective heat transfer with the surrounding air. Within our research group at ETH Zurich, we are developing computational workflows for predicting temperature fields in machine tools using computational