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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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, their achievements and productivity to the success of the whole institution. At the Faculty of Mechanical Science and Engineering, Institute of Manufacturing Science and Engineering, the Chair of Forming and Machining
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Further information Hochschule Offenburg Department of Electrical Engineering, Medical Engineering and Computer Science: Institute for Machine Learning and Analytics Institute of Reliable Embedded Systems
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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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positions (TV-L E13). Addressing global challenges, the school provides a wide variety of topics, from logic in autonomous cyber-physical systems to machine learning in Earth System models. You will have one
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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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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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mathematical modeling to simulate water fluxes and biogeochemical processes related to carbon and nitrogen cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset
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) in materials science, physics, chemistry, electrical engineering (or a similar discipline) with focus on sensorics; experience in data processing and machine learning; experience in 2D materials