46 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" Postdoctoral research jobs at Aarhus University in Denmark
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quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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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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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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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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in the areas listed here: https://math.au.dk/en/about/vacancies/postdoc/ When applying, you will be asked to indicate, which of the areas listed on the page above are of interest to you. The list
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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grasslands and evaluation of land-use intensity, Expertise in classification with machine-learning methods, statistics, spatial analysis and land-use modeling, Experience and interest in conducting fieldwork
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the described area. Take the initiative in developing the research field and collaborate with national and international academic and industry partners. Teach and supervise students at the bachelor’s, master’s
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. Researchers in the section teach the BSc and MSc programmes in animal and veterinary science and supervise PhD students and conduct research-based public sector consultancy for national and international