104 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions 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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). Strong background in stochastic optimization, machine learning, or mathematical statistics. Track record of publications in relevant journals/conferences (ICML,NeurIPS,ICLR,COLT, Siam Journals, JMLR, COAP
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within Mathematics. The positions have 1st September 2026 as earliest possible start dates. There are postdoc positions available in the areas listed here: https://math.au.dk/en/about/vacancies/postdoc
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abroad. We also teach philosophy and history of ideas in combination with a minor subject, which qualifies students for teaching in Danish upper secondary schools. See more at https://kandidat.au.dk
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university, seeks top students for attractive PhD stipends. The call is open until 1 February, 2026, with the earliest start date, 1 May, 2026. Please find more details and apply at https://math.au.dk/en/about
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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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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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to the research and infrastructure in the Plant Molecular Biology section (https://mbg.au.dk/en/research/research-areas/plant-molecular-biology ). Internal communication and teaching at the Department is primarily