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statistical methods for modelling and data treatment engage in teaching, innovation and advisory activities in relation to food technology, food chemistry, and food nutrition in a broad sense. Teaching
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statistical methods for modelling and data treatment engage in teaching, innovation and advisory activities in relation to food technology, food chemistry, and food nutrition in a broad sense. Teaching
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, scipy, scikit-learn, pytorch, pytorch geometric, etc.). Proficiency in statistics and graph machine learning, including the ability to build and deploy models, and evaluate their performance. Software
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advanced materials. Experienced in both strain development and related modelling & data analysis. Experienced with processes of biomanufacturing, including fermentation, downstream processes and scale-up
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. Experienced in both strain development and related modelling & data analysis. Experienced with processes of biomanufacturing, including fermentation, downstream processes and scale-up. Proven leadership in
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, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position. DTU National Food Institute DTU National Food
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, consisting of (a) remanufacturing processes, (b) take-back systems, (c) design for disassembly and circularity, (d) business models, and (e) sustainability and circularity assessment. The project will analyse
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are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates
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. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates
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simulate wind and solar forecast uncertainties on pan-European level, leveraging latest machine learning weather forecast models Apply machine learning methods to forecast day-ahead and balancing market