141 computer "https:" "https:" "https:" "https:" "University of St" "St" positions at ETH Zurich
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energy transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal
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-facturing processes. In this internship, you will work on state-of-the-art anomaly detection methods using computer vision and time-series data, with a particular focus on multimodal data fusion for powder
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technologies (i.e. computing, data, algorithms, AI) in society. We are in particular looking for candidates who have interest and experience with STS and humanities pedagogy in the context of a technical
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. Joël Mesot. The closing date for applications is 22 February 2026. We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://ethz.ch/en/the-eth-zurich/working
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environment where philosophy meets data science, public health, medicine, and law? At the Health Ethics & Policy Lab (https://bioethics.ethz.ch ), you will join a team committed to shaping responsible
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received by 1 November 2025. Note: as an option, one of the four reference letters can be about teaching. For more details, please see the website: https://math.ethz.ch/fim/postdocs.html Application
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of history, philosophy or neighbouring humanities disciplines (such as STS, cultural studies, social anthropology). The starting date is around September 2026. The position is for two years with
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understanding of the aging of solid insulation under mixed-frequency medium-voltage stress, see https://doi.org/10.1088/1361-6463/acd55f for a relevant example research work of our team in this area. Profile
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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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-scale geospatial and Earth system datasets, within the NCCR CLIM+ program. The role bridges climate science and AI, developing novel methods for climate data analysis, downscaling, and synthesis using