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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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gathered from sites in five different languages – English, Spanish, Italian, Korean and Indonesian. This analysis can provide a wealth of information about the characters in a story, the genre, what a story
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information, see also our diversity policy webpage: https://www.rug.nl/about-ug/policy-and-strategy/diversity-and-inclusion/ Our selection procedure follows the guidelines of the Recruitment code (NVP): https
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information, see also our diversity policy webpage: https://www.rug.nl/about-ug/policy-and-strategy/diversity-and-inclusion/ Our selection procedure follows the guidelines of the Recruitment code (NVP): https
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of our teaching and research. We therefore invite applicants from underrepresented groups in particular to apply. For more information, see also our diversity policy webpage: https://www.rug.nl/about-ug
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academic debate and contributes to the quality of our teaching and research. We therefore invite applicants from underrepresented groups in particular to apply. For more information, see also our diversity
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sustainable way of dealing with their health conditions. The technical challenge within this project lies in the huge variance of the data. Furthermore, the app needs to be able to work with sparse incomplete
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information about working conditions and working for the University of Groningen, please check: https://www.rug.nl/about-ug/work-with-us/ You will initially be appointed for a period of 1 year with
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quickly derive the necessary information from noisy, incomplete, real-world data. Furthermore, the algorithms to be developed within this project will be implemented on automated beds that provide fully