230 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"UCL" positions at ETH Zurich
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80%-100%, Zurich, fixed-term The Department of Management, Technology, and Economics (D-MTEC) at ETH Zurich is looking for an Recruitment & Admissions Manager (80% - 100%) for a 1-year contract
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: Must hold a master’s degree in computer science, data science, or a closely related field Have strong analytical and problem-solving skills Are able to work independently and take ownership of technical
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, the research group has investigated effects of trainings that help people recognize misleading data visualizations, thereby reducing their negative impact on information extraction (for example, see Rho et al
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Computer Science, Biomedical Engineering, Data Science, Cognitive Science, or a related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series
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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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challenges. The work is conducted at the interface of mechanics, artificial intelligence, and computational science. The developed methods will be validated on benchmark problems and real-world data and
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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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or mechanical engineering, or CS Solid knowledge of computer vision and ML, particularly anomaly detection methods Experience with multimodal data (e.g., image + time series, sensor fusion) is a strong ad-vantage
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of mathematics, computer science, and evolutionary biology. We develop methods to understand evolutionary, ecological, epidemiological, and developmental processes on different scales based on genetic data. In our
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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