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and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover
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screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot
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2019, unites top PhD students in all areas of data-driven research and technology, including scalable storage, stream processing, data cleaning, machine learning and deep learning, text processing, data
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