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Field
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insights into algorithms and discretization techniques – critical for numerical computations and simulations. This convergence signifies a pivotal phase in the mathematical sciences, where the divide between
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Theory, Statistical Inference, and Information Geometry. (2) Computing for AI: Programming Language Theory, Algorithm Theory, Combinatorics, Optimization Theory, and Homomorphic Encryption. (3) AI
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, materials science, or related fields. You must have proven expertise in at least one of the following fields: computational geometry, algorithm development, machine learning for image recognition
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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computational counting and sampling, including developing new algorithms and analysis techniques. Typical tools and topics are Markov chains Monte Carlo, Lovasz local lemma, high dimensional expanders, geometry
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of Mathematics and Computer Science, and other research sections at the department are Algorithms Computational Science Data Science and Statistics Geometry, Topology and Algebra Learning Experience Design The
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University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry and Machine Learning, with a focus on studying geometric structures in data and
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sensing; support in choosing tip geometry, stud magazine, and interfaces to the vacuum chamber). • Co-development of algorithms for optimal welding (trajectory and force planning, adaptive parameters
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at the Institute of Visual Computing, course on Fundamentals of Geometry Processing, or Data Structures and Algorithms. Co-supervision of bachelor and master thesis. Research and development
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) Academic Disciplines: Pure mathematics: algebraic geometry, differential geometry, partial differential equations, number theory, probability. Theory of Computing: all areas of theoretical computer