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Description Join us in seeking exciting new developments using graph theory in nearest neighbor models for active matter! Do you enjoy working with graph theory, and seeing how functions on graphs can inform
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. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains. The position is hosted in the Leibniz Junior Research Group
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to model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
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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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Profile: We seek someone with strong mathematical maturity in control theory, dynamical systems, or applied mathematics. Familiarity with nonlinear systems analysis, graph theory, and formal methods (e.g
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, tasks have a continuous evolution, and the precedence graph becomes dynamic. There is an initial method proposed in the literature, where a static model is proposed, introducing two states of products
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supervised by Sebastian Throm. The subject area of the announced position covers kinetic theory, non-local diffusion and dynamics on graphs. The precise research direction will be determined together
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Apply now The Mathematical Institute (MI) of Leiden University and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a PhD Candidate in Random Graphs and Complex Networks
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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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the context of algorithmic problems related to constraint satisfaction and graph homomorphism and isomorphism problems. It brings to bear significant new mathematical (algebraic and topological) methods