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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, the QCILab
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projects that may involve concepts and priorities such as knowledge-graph-driven data integration, AI-powered literature review, agentic database search assistants, multi-omics analysis tools, life sciences
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and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills include: Strong foundation
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Job Posting Title: Post Doctoral Scholar The Opportunity Lead and contribute research on multimodal data integration, ontology and knowledge graph building for energy domain. Supervise graduate and
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brings together leading researchers in algebra, combinatorics and related disciplines, including finite geometry, algebraic graph theory, permutation group theory, coding theory and extremal combinatorics
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) diversity, (v) online controlled experiments, and (vi) network science. The ideal candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science, Computer
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systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics and mathematical approaches to signal analysis
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software components; Publish research results in high-quality international journals and conferences; Collaborate with researchers, a PhD candidate working on polyvocal knowledge representation, curators
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, Murray Cole, and Hugh Leather; https://doi.org/10.1109/CGO.2019.8661174 What you will do Develop theory aimed at applying concepts around bisimilarity to control flow graphs, with an eye towards
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models, stochastic processes on networks and graphs, network communication processes, and reports. The fellow will work with the other SUPPORT fellows to develop statistical methods and data resources