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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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interest in data-intensive systems. You bring a solid foundation in software or data engineering, typically developed through a Master’s degree or higher (e.g. PhD) in Computer Science or a related field, or
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100%, Zurich, fixed-term The Swiss Seismological Service (SED) at ETH Zurich invites applications for a PhD position within a multi-year applied research project on the detection, localization and interpretation of explosion events in underground ammunition storage facilities. The position is...
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. Céline Labouesse. The position is subjected to admission to the doctoral program at D-MAVT. Profile We are looking for : a curious and resourceful individual, with a pronounced taste for interdisciplinary
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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
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100%, Zurich, fixed-term Are you passionate about advancing the frontiers of resilient navigation to tackle the growing challenges of signal interference? Are you an expert in GNSS processing, eager to integrate cutting-edge multi-sensor fusion and AI technologies? Join our young and dynamic...
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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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datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
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years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep-learning models on distributed systems