163 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"P"-"UCL" positions at ETH Zurich
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transfer, developing and employing laboratory experiments, computer simulations, and field analyses. Our aim is to gain fundamental insights and to develop sustainable technologies that address societal
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100%, Zurich, fixed-term Are you a data-savvy innovator eager to tackle pressing challenges in livestock sustainability? The Animal Nutrition Group at ETH Zurich is hiring a talented Postdoctoral
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, we collect data through biological monitoring, environmental DNA methods, remote sensing, and field sampling, and use these data to answer questions with statistical and process-based models
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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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core part of your project will be interpreting the data and developing scientific hypotheses about the atmospheric processes that control the cycling of selenium and other trace elements. You will work
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, data-driven frameworks that enable robust monitoring and condition assessment of infrastructure fleets. By combining smart sensing with distributed intelligence and advanced stochastic modelling
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, and certificates Names and contact details of two referees Further information about the research group can be found on our website . Questions regarding the position should be directed to Prof. Dr
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, 4-year project "LOCO-DC" - Locational optimization of data centers in multi-energy systems, led by Dr. Fabian Heymann, Senior Researcher at ESA. The proposed research project will develop and apply a
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management and the abandonment of agricultural land. Another part of your job will deal with the biodiversity implications of re-wilding, based on data from multiple WILDCARD partners as
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tracking of minimally invasive robotic systems Autonomous control in uncertain anatomical environments Computer vision for image-guided robotic procedures (incl. endoscopic, MR-, US-guided) Surgical training