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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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related field Sound knowledge in the field of artificial intelligence and machine learning Ideally experience with knowledge graphs, semantic search, graph neural networks (GNNs), explainability
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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
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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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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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