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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models
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code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and
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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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with respect to high level research, training and innovation within manufacturing engineering, in an exciting combination of academic and industrial environments. The selected candidate will receive
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that: You have an open mind and can think creatively in a computational and/or programming context. You are interested in combining your physics-based modelling skills with data-driven analysis
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to a two-year master's degree. You will work in a research team combining manufacturing engineering, solid mechanics, experimental methods and analytical/numerical modeling. A longer period at a
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interdisciplinary center at DTU dedicated to merging life sciences, automation, and data-driven innovation to revolutionize research and development. The program combines the expertise of five DTU departments