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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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are meteorology, mesoscale modelling, analysis and interpretation of meteorological datasets. We are also interested in hearing from researchers with oceanographic, as well as meteorological, science background
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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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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engage in collaboration with industry and authorities. You must contribute to the teaching of courses. DTU employs two working languages: Danish and English. You are expected to be fluent in at least one