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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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, computational fluid dynamics and material science, dynamical systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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graph theory. Qualifications Candidates with a Ph.D. in any area of cognitive neuroscience broadly defined (e.g., Psychology, Neuroscience, Computer Science, or a related field) are welcome to apply
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investigator and Postdoctoral scholars/fellows on the status of research. Collect and log laboratory results, clinical outcomes and/or survey data. Evaluate and perform data analysis using graphs, charts
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the theory of quantum graph states. Additional expertise in computational methods would be useful but is not necessary. The Postdoctoral and Senior Research Associate positions will also involve
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Lab (MaTRIX Lab) develops advanced computational and AI methodologies to decode complex biological systems and accelerate discoveries into translational impact. The lab integrates deep learning, graph
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
with biomedical data, including clinical, EHR, omics, and imaging Knowledge graphs (KGs), and integrating LLMs with KGs Multimodal LLMs Special Physical/Mental Requirements Special Instructions
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Responsibilities Research: - Conduct research in AI reasoning, semantic modeling, and knowledge graph development. - Develop and optimize graph databases for structured knowledge representation. - Apply neural
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of the Postdoc Research Fellows are the following: Research: Work on novel AI/Data Science research with crucial interdisciplinary scope using machine/deep learning, generative/agentic AI, and knowledge graphs