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“PhD application for Self-supervised Learning of Time Series Data” in the subject line. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
31.07.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, is inviting applications for a fully funded PhD position at the Technical University
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16.07.2025, Wissenschaftliches Personal A PhD position (75% TV-L E13, to be extended to 100% after 8 months) in discrete optimization is available at the Professorship of Optimization and
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to an internationally competitive PhD degree and internationally peer-reviewed publications. The position will include significant involvement in selected nationally and internationally funded projects, such as various
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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. The research group Mechanoreceptors/ Section II at Leibniz-LSB@TUM is currently looking for a PhD student (m/f/d) to start as soon as possible. The position is to be filled on a part-time (65%) basis