223 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Postdoctoral positions in Denmark
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(e.g. using COBRApy or related toolboxes), or a strong motivation to develop this expertise. Data science, AI/ML, and digital surrogate models Experience with data science and machine learning, including
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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
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systems. Further information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/ . Inquiries about the position can be made to Assoc. Prof. Leonardo Midolo
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biogeochemical modelling and data-driven machine learning approaches at an ecosystem scale to improve our understanding of the fate of nitrogen fertilizers applied to agricultural soils. This understanding will be
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for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. You can read about the recruitment process at https://employment.ku.dk/faculty
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research profile within organisational studies, Computer-Supported Cooperative Work, Human-Computer Interaction or related research areas as documented by a PhD dissertation and/or research publications
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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
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requirements, including link budgets, beam steering, and orbital pointing dynamics. • Experience with optimization methods and physics-informed machine learning. • A strong publication record in antennas
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are expected to: shine in individual and collaborative research, either to assist groups of bachelor’s students in doing homework or co-teach advanced courses relevant for your research area. The
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expected to: shine in individual and collaborative research, either to assist groups of bachelor’s students in doing homework or co-teach advanced courses relevant for your research area. The Department