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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description [Background
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: The successful applicant will be responsible for: Obtaining rigorous mathematical results at the interface of optimization, geometry, and data science Designing, implementing, and testing algorithms Engaging in
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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Mathematical physics, spectral theory Evgeny Strahov Random matrix theory, integrable probability Yakov Varshavsky Representation theory, Algebraic geometry, Geometric aspects of Langlands program Tamar Ziegler
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; proficiency in graph data structures and algorithms for geometric analysis; advanced knowledge of surface representation math; experience in writing geometry translators for complex surface features; excellent
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of Computation, Information and Technology (CIT), located on the Garching Campus, starting October 01, 2025 or later. The group is seeking a highly qualified candidate for a postdoctoral position who possesses
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PhD Research Fellow in Hydrogen Safety:Hydrogen Explosions in Complex Geometries Apply for this job See advertisement UiB - Knowledge that shapes society Through robust and close interaction with
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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with several research groups working in related fields, particularly in algebraic geometry and algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data