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Field
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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on Topological methods in Discrete Mathematics and conduct research related to problems in Combinatorics, Graph theory and aspects of the Constraint Satisfaction Problem (CSP) with emphasis on topological methods
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work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate offerings available, 30 lead to a doctoral degree. Connections
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Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and
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are, for instance, active in the fields of incidence geometry, abstract polytopes, discrete optimization, graph theory, convex polytopes, non-commutative algebra, (non-commutative) algebraic geometry, homological
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Group (ECOPRO) Fellowship Type: Postdoctoral Fellowship Location: Daejeon, Daejeon 34126, Korea, The Republic of [map ] Subject Areas: Extremal and Probabilistic Combinatorics, Graph Theory, discrete
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Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation of Correlated
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Type: Postdoctoral Fellowship Location: Daejeon, Daejeon 34126, Korea, The Republic of [map ] Subject Areas: Discrete Math, Structural Graph Theory, Extremal Graph Theory, Matroid Theory, Combinatorics
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to students pursuing degrees through the doctoral level. More than 20 percent of its 25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory
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graph theory, for example with graph-based methods would be considered an asset. Experience with data collection and hardware setup; prior hands-on hardware development would be considered an asset