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and Boulton, 1968; Wallace and Dowe, 1999a; Wallace, 2005) is a Bayesian information-theoretic principle in machine learning, statistics and data science. MML can be thought of in different ways - it
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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has a strong PhD program in Applied Mathematics, Applied Statistics, Graph Theory/Combinatorics, and Analysis, featuring active research collaborations both within the University and with external
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applications in the field of Galois Geometry and Applications within Coding Theory and Graph Theory. Women and minorities are encouraged to apply. Academic education You will participate as co-responsible in
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statistical physics. Specific Requirements Preference will be given to candidates with experience in research related to machine learning, graph theory, statistical physics, and modeling of stochastic systems
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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab , the 6GSPACE Lab , the HybridNetLab
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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relevant expertise: A PhD in Computer Science or a closely related field, with specialization in Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph
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programs. Alternatively, Mathematics, Computer Science, Computer Engineering, Electrical Engineering, or a similar field; Strong mathematical background: basic knowledge of graph theory and excellent
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a similar field; Strong mathematical background: basic knowledge of graph theory and excellent background in linear algebra, finite fields and rings; Strong background in digital hardware design and