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of computational approaches to large scale simulations Basic knowledge of (geo)chemical processes and machine learning will be of advantage Expertise in Machine Learning approaches, ideally beyond neural networks
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ranges from core areas of computer science and electronics over medical applications to societal aspects of AI. SECAI’s main research focus areas are: Composite AI: How can machine learning and symbolic AI
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defects of smectic-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this
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the distribution of water vapor by means of machine learning approaches and to improve atmospheric correction beyond standard approaches. The research work is expected to contribute in two ways: (i) the separation
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modern models beyond the worst case e.g. integrating machine learning into algorithm design. We are looking for candidates with a strong mathematical background, an excellent degree in mathematics
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of the German Armed Forces Munich), the DLR (German Aerospace Center) with its Oberpfaffenhofen institutes, and the BHL, the Bauhaus Luftfahrt. This pooling of research, graduate programmes and teaching merges