60 deep-learning-phd-"Computer-Vision-Center" Postdoctoral positions at Aarhus University in Denmark
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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 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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decomposed into modular sub-components that can be either process-based models and/or deep learning models. MCL has the flexibility to replace any uncertain process description with a deep learning model
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Science, Computer Engineering, Artificial Intelligence, Physics, Mathematical Engineering, Mechanical Engineering or similar. Relevant skills: Strong background in machine learning/data science. Deep knowledge
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employees, 500 PhD students and 160 technical/administrative employees who are cooperating across disciplines. As a Postdoctoral researcher, you will be working at Aarhus University Hospital or another
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leading academic and industry partners within the Horizion Europe Project. Your profile We are looking for a highly motivated and talented candidate with a background in deep learning. The required
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environmental changes, agricultural management, and ecosystem sustainability Experience with deep learning, radiative transfer modeling and ecosystem modeling Teaching and supervision experience Who we
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tools or functional genomic information or OMICS to improve genomic prediction models. The persons hired will collaborate with industry partners, teach at undergraduate and graduate levels, and supervise
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these experiences teach them lessons about their own fit in politically powerful positions. The two positions advertised in this call focus primarily on the second work package. The YOPOW research project runs
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engineering, data science, statistics, mathematics, physics or an adjacent subject, with focus on medical image analysis and/or deep learning. Furthermore, the following competences will be expected