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laboratory-scale turbines. Combined with modern measurement methods, these facilities offer ideal conditions for addressing real-world wind energy challenges under controlled laboratory settings. The position
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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Description The Soft Matter Physics Group at the University of Tübingen is searching for a PhD student / doctoral candidate in Physics, Machine Learning and advanced X-ray and neutron scattering (m
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looking for a PhD Student (f/m/d) in Machine Learning for Quantum Computing and Simulation of Quantum Matter. The Scope of Your Job The successful candidate (f/m/d) will be part of the interdisciplinary
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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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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chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive
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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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quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent spoken and written English and the
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In