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industry, with the REACT program serving as a strong foundation for their future success. Position and Requirements: At the Chair of Compiler Construction, we have a long-term vision of shaping how future
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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. Its lean governance structure supports an agile and efficient implementation of its vision. Its sustainable, 37-hectare and partly residential campus will form the heart of a new district in Nuremberg
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! We
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Learning" team has AI expertise and we have a high-performance IT infrastructure available. For our "Computer Vision and Machine Learning" team, we are looking for a student assistant as soon as possible
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Since 2020, Fraunhofer Heinrich Hertz Institute has worked with United Nations
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-tracking technology, Computer Vision, Speech/ Language Processing, VR, and AR. • Know-how/Interest in designing user studies. • Excellent communication skills and a collaborative spirit to work with