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experience with PyTorch. Ideally, knowledge in computer vision and object detection/segmentation. Motivation to independently delve into new and current research topics. Willingness to work with erotic
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21.05.2026, Academic staff This PhD project, which is part of the Elite Network Bavaria-funded graduate college “The Proteomes that Feed the World” at the TUM School of Life Sciences, focuses
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-film electrodes Fabrication of electrochromic cells What you contribute A current Master’s degree programme in the natural sciences (preferably chemistry, materials science, physics or nanostructure
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, biologists, and computer scientists at the Universities of Tübingen and Hohenheim and the Senckenberg Institution of Biodiversity and Earth System Research in Frankfurt, investigating how the interactions
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plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov solvers
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Profile • Completed Master’s degree (or equivalent) in social psychology, computational linguistics, computational social science, linguistics, communication science, or a related field with a strong
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the area of strategy&technology. Here, we research, among others, the influence of artificial intelligence on corporate strategies, the integration of AI in strategy processes, and the importance
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skills, preferably some experience with PyTorch. Ideally, knowledge in computer vision and object detection/segmentation. Motivation to independently delve into new and current research topics. Willingness
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. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing robust, user
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to improving the understanding of the lunar water cycle, with many applications in the field of solar system science and exploration. To this end, we combine both numerical modelling and experimental methods and