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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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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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networks, 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
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are passionate about any or all of the following: Data Science, Computational Social Science, Behavioral Economics, Human-Bot interaction, Experimental Research, Game Theory, and Artificial Intelligence. Some of
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: extremal graph theory, Ramsey theory, probabilistic combinatorics. • Candidates should have (or be near completion of) a PhD in mathematics. • Candidates should have a strong research record in Combinatorics
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and geometry on groups, harmonic functions, opinion dynamics and other stochastic processes on graphs Gil Ariel Bacterial swarming, collective motion in nature, stochastic thermodynamicsActive matter
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and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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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