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19.09.2023, Wissenschaftliches Personal The Bienert Lab is part of the TUM School of Life Sciences of the Technical University of Munich located in Freising-Weihenstephan. The main objective
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to understand how grazing influences tropical and subtropical grassland productivity and their stability, aiming to detect indicators of early restoration success. This work is conducted in collaboration with
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), restriction of processing (Art. 18 GDPR) and objection to processing (Art. 21 GDPR). If you have any questions, you can contact the LIR data protection officer (datenschutzbeauftragte@lir-mainz.de). You also
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conduct experiments in the field to understand how grazing influences tropical and subtropical grassland productivity and their stability, aiming to detect indicators of early restoration success. This work
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
approaches for sustainability, new concepts for security and solutions for current latencies in communication networks. Find out more about the project under https://6g-life.de/ About us: At the Chair
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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research into novel sensors and discover their applications. A core tool of the group are diamond quantum sensors for magnetic fields. Your project You will spearhead one major research effort of our lab
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News Detection Topic / Area: The positions are flexible in terms of research direction within 3D vision with a heavy focus on cutting-edge deep learning-based techniques. We are particularly interested