210 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "St" "St" uni jobs at ETH Zurich in Switzerland
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100%, Zurich, fixed-term The postdoctoral researcher will advance the application of AI, large language models (LLMs), and machine learning to extract trustworthy climate information from large
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research groups at ETH Zurich, the Swiss Data Science Center and Agroscope. The overall objective of PhenoMix is to test the hypothesis that current high throughput field phenotyping (HTFP) technology in
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and networking platform to support the development and application of Earth system, weather, and climate modeling, data infrastructure, and impact research. Project background There is an ever
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novel multi-encoder-decoder architectures capable of ingesting various satellite data streams (e.g. radiances, cloud products, lightning observations, hyperspectral soundings) and integrating them
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paradigms in human participants Acquire multimodal data in human participants, including pupillometry, behavioral measures, and fMRI Integrate real-time pupil-based self-regulation into adaptive learning
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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quality Surrogate Modeling: Building, training, and evaluating machine learning surrogate models to emulate complex seismic behaviors and accelerate forecasting Data Engineering: Populating and managing
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data collection, data processing, algorithm development and system optimization. Job description Experimental Campaigns and Sensor Evaluation: Design and analysis of controlled test explosions in
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psychologists, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU
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100%, Zurich, fixed-term We invite applications for a PhD position on Data-driven and hybrid hydrological modeling co-supervised by Manuela Brunner (ETH Zurich, WSL) and Olivia Martius (University