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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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(density functional theory and ab-initio molecular dynamics simulations) with artificial intelligence techniques to parameterize machine learning force fields and kinetic Monte Carlo methods to model
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life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health
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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab
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long-lasting adverse health effects in humans and wildlife is also performed. For more information see www.iob.uu.se Data-driven life science (DDLS) uses data, computational methods and artificial
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. The PhD position is within the Data-driven life science (DDLS) Research School. DDLS uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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. The data-driven life science initiative Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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School. DDLS uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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projects that involve data analysis, the application of artificial intelligence, the development of new detection techniques, and the exploration of new experimental methods through collaboration with our
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and near infrared, mid infrared and advanced machine learning and artificial intelligent modelling to enable accurate monitoring of nitrogen mineralization rate to enable understanding and improving