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-driven (machine learning) and model-driven techniques. As part of the DFG research project “Progressive, Spatio-Temporal Consistent Inline Activity Reconstruction and Recognition,” a doctoral position is
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-driven (machine learning) and model-driven techniques. As part of the DFG research project “Progressive, Spatio-Temporal Consistent Inline Activity Reconstruction and Recognition,” a doctoral position is
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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25 Sep 2025 Job Information Organisation/Company Universität Siegen Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Country Germany Application
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of services: Promotion of own scientific or artistic qualification according to the Wissenschaftszeitvertragsgesetz [act on temporary employment in higher education] (e.g. PhD) Diverse opportunities to take on
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knowledge in one or more of the following areas is desirable: 3D scene reconstruction and machine learning, visualization, hardware-accelerated simulation Our range of services: Promotion of own scientific
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knowledge in one or more of the following areas is desirable: 3D scene reconstruction and machine learning, visualization, hardware-accelerated simulation Our range of services: Promotion of own scientific
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an equivalent field of study (preferably with a focus on telecommunications, communications engineering, or related areas). Strong intrinsic motivation to pursue a PhD degree and conduct independent scientific
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of services: Promotion of own scientific or artistic qualification according to the Wissenschaftszeitvertragsgesetz [act on temporary employment in higher education] (e.g. PhD) Diverse opportunities to take on