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Field
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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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, and maintaining a system to track proposals. Evaluate and perform preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research results collected in
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, and (b) the critical role of structural and functional connectivity using combined tractography and graph theory analyses. Our modeling of mnemonic representations uses the latest tools available to AI
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, and analysis by using concepts and methods from machine learning, including pattern recognition, graphs, and complex networks. ** Specific Research Areas: * Develop concepts and algorithms to analyze
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chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in high dimensions. About the role You will
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surrogates of electronic Hamiltonians. The postdoctoral researcher will develop graph neural networks based on the MACE architecture to predict Hamiltonian elements for 2D materials and van der Waals
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collaboration with Growgraph, an R&D startup engaged in advancing knowledge graph technologies and AI-driven methods for structured data analysis. This partnership aims to foster the transfer of research outcomes
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chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in high dimensions. About the role You will
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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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chains, random graphs and trees, random matrix theory, stochastic and Lévy processes in infinite-dimensional spaces, free probability, random sphere packings in high dimensions. About the role You will