208 data "https:" "https:" "https:" "https:" "UNIV" "Embry Riddle Aeronautical University" positions at ETH Zurich
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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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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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-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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, 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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of emerging technologies balanced against their dark sides. Our research at the intersection of data, behavioural, and computer science draws on data from real-world and experimental settings The Centre for AI
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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