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in Computer Science or a related field Experience in software development Excellent programming skills Familiar with basics of machine learning Interest in mobility technology and/or simulations, with
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machine learning potentials for supramolecular metallacages and enzymes. Efficient and accurate potentials will be developed and applied to study confinement effects in metal-containing systems, such as
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on knowledge representation and machine learning at scale. It is particularly interested in models with rich semantics, e.g., RDF knowledge graphs. You will be supervised by Prof. Dr. Axel Ngonga (head of group
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the complex food composition, which can lead to masking effects and molecular interactions in the food matrix. The applicant will work on the development of machine learning prediction models
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Ghahramani. Course web page . 4F10: Statistical Pattern Processing Taught by Mark Gales. Course web page . 4F13: Machine Learning Taught by Zoubin Ghahramani and Carl Rasmussen. Course web page . PREVIOUS
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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19.04.2024, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Computer Engineering at TUM has open positions for a doctoral researcher (TV-L E13 100%, 3-4 years
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, direct electroreduction (electrolysis) and plasma synthesis. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and
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is expected An excellent mathematical background and experience in software development is required Experience in developing and applying statistical and/or machine learning-based computational methods