577 machine-learning-"https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" positions in Austria
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starting: 15.05.2026 | Working hours: 30,00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: Job ID: 5515 Explore and teach at the University of Vienna, where more than
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and flexibility. We cover the whole data processing chain including image capture, image processing/computer vision and image content analysis with traditional and modern machine learning/AI methods
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data processing chain - from image capture, image processing/computer vision to image content analysis - using both traditional and modern machine learning and AI methods. Your qualifications as an
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Expertise in one of the following areas applied to sports and/or human movement science: Computer Vision Match & Performance Analysis Machine Learning Ubiquitous Computing Virtual Reality Teaching experience
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the Job related to staff position within a Research Infrastructure? No Offer Description 40 hours/week | limited to 2 years The Center of Artificial Intelligence & Machine Learning (CAIML) research
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data processing chain - from image capture, image processing/computer vision to image content analysis - using both traditional and modern machine learning and AI methods. Your qualifications as an
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this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a
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topics in theoretical chemistry, from the use of advanced electronic structure methods to the development of dynamical approaches to study photochemical reactions, also including machine learning
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hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a large initiative
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ID: 5335 Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see