139 computer-"https:" "https:" "https:" "https:" "University of St" "St" "St" positions at ETH Zurich
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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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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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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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. 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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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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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi