113 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "I.E" Postdoctoral positions in Denmark
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Introduction The Department of Economics at the University of Copenhagen (UCPH, https://www.econ.ku.dk/ ) invites applications for a two-year postdoctoral position in econometrics and causal
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connection of renewable generation, experience with HIL systems and experimental test setups, and strong competences in communication systems as well as coding experience (C++ and Python). As a formal
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structure quantification by tomography and imaging Perform testing across different scales, i.e. characterizing the viscoelastic properties of the base material and the nonlinear mechanics of the scaffolds
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. The ideal candidate will have: Experience in developing novel algorithms. Experience in coding in python and preferably C/C++. Experience in frontend engineering, including but not limited
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published papers) with the above topics. A high level of coding competences will be beneficial. If your PhD is not yet completed, please document that your thesis will be submitted before the start date
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. Software or code development, incl. artificial intelligence and machine learning. Automation and robotics, incl. safe human-machine interaction. Serious gaming, incl. AR/VR. Life cycle analysis. You are
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
ecological processes, i.e., vertical turbulent diffusion, phytoplankton production and consumption, greenhouse gas emissions, etc., to develop hybrid models. Performance will be compared to several 1D aquatic
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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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are expected to have a strong background in marine hydrodynamics or related fields, along with substantial experience in code development and numerical modeling. The role requires a proactive approach
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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