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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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Postdoctoral Position in Probabilistic Machine Learning for Spatio-Temporal Data Modelling A postdoctoral position is available at the Department of Computer Science, Aalborg University Copenhagen
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). This position focuses on the machine learning methodology of the project, aiming to: Develop probabilistic spatio-temporal models that integrate uncertainty from climate projections into land-use forecasts
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and have synergiccollaborationeffects. Weexpect a motivatedearlycareer researcher with stronginterest and experience with GIS/earth observation/climateprojection data as well as machine learning models
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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but
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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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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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employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research