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develops predictive, multi-scale computational frameworks to guide sustainable microbial food production. By coupling data science with mechanistic models, this collaboration between universities, research
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. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive
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, and ambitious researcher committed to accelerating the green transition by advancing adaptive materials, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery
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at DTU within the BUG-ID network (DCs 2, 3, 12, 13): DC2: Infection biomarker discovery in chronic wound models DC3: Infection biomarker monitoring in environmental samples DC12: Optimizing bioreceptor