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inequalities and Sobolev-type spaces (with Hytönen and/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic
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-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be
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expertise: A PhD in Computer Science or a closely related field, with specialization in Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph theoretic
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and Sobolev-type spaces (with Hytönen and/or Korte), Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game
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encouraged to apply: • Optimization (deterministic, stochastic, robust, reinforcement learning–based) • Systems architecture and design for complex socio-technical systems • Graph theory, network science, and
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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of groups that are of interest in the context of rigidity, group cohomology, noncommutative geometry and index theory, harmonic analysis on groups, expander graphs and high-dimensional expanders. Required
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 month ago
No. 2083, id.2294) and a research team at the University of Glasgow led by Leroy Cronin that utilizes graph theory to explore molecular complexity (Philosophical Transactions of the Royal Society A
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/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing