8 machine-learning-"https:"-"https:"-"CEA-Saclay" Postdoctoral positions at Aarhus University
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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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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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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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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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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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. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
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helium droplet machines. Also, you will be jointly responsible for making sure that various experimental apparatus in the laboratories are maintained and serviced with timely care. In particular
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frameworks for disorder and property fluctuations will be considered and can compensate for limited prior experience in fracture mechanics. You should be motivated to learn new theories and to integrate them