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hosts. The project is centered on the integration and analysis of multiomics datasets utilizing advanced machine learning approaches and biological network analysis. The successful candidate will join an
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Your Job: In this position, you will be an active member of our "Simulation and Data Lab for AI and Machine Learning in Remote Sensing", which aims to strengthen interdisciplinary research by
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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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Bewerbungsende: 15.09.2025 The AI4Science Group (former Computational Molecular Biology - head: Frank Noé) is an interdisciplinary research unit active in the development of machine learning methods
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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of the hazardous space radiation environment and developing tools for the prediction of the adverse effects of the space environment utilising satellite observations, physics-based numerical models, machine learning
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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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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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. The candidate will also collaborate with the Department of Computer Science at Kiel University and the remote sensing company EOMAP GmbH, employing state-of-the-art machine learning techniques to improve
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Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied Mathematics, headed by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning