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Posting Information Posting Number FAE1689 Advertised Title Assistant Professor in Combinatorics & Graph Theory Campus Location Main Campus (Memphis, TN) Position Number 001954 Category Full-Time
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advancement of the research of deep neural networks, in the field of adaptive processing of graph data (Deep Graph Learning). The project includes the following strongly interconnected fundamental research
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solving problems at the boundaries of machine learning, graph theory, and algorithmics. Your future tasks: You actively participate in research, teaching & administration, which means: You are involved in
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). "Statistical field theory applied to complex networks” "Quantum geometrogenesis – Graph theoretic approaches to building spacetime” web page For further details or to discuss alternative project arrangements
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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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Omer Ben-Neria Logic, set theory Shai Evra Graph theory, representation theory, number theory Adi Glucksam Complex analysis, potential theory, and dynamics Or Hershkovits Geometric analysis
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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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://jarvis.nist.gov/) infrastructure uses a variety of methods such as density functional theory, graph neural networks, computer vision, classical force field, and natural language processing. We are currently
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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the opportunity to apply computational theory to real-world biomedical research challenges within a collaborative academic environment. The incumbent will contribute to the development, implementation, and