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The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
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at the top venues of machine learning research. Responsibilities and qualifications You should have prior experience with machine learning from both a theoretical and practical perspective. Experience in one
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enthusiastic scientist with the following competencies and experience: Essential experience and skills: You have a PhD in Machine Learning, Artificial Intelligence, Bioinformatics, Biostatistics, Epidemiology
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data from existing cohorts and national registries, applying novel machine learning methods. The specific work tasks will include data management of large studies, scientific work related to the topics
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving
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expect the candidate to have: PhD in transportation science, machine learning, behavioral economics or a related field. Programming skills Python, along with experience working with transportation
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-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and