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this interdisciplinary project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
knowledge graphs. Your work will support the creation of FAIR-aligned metadata (including emerging standards like Croissant) to ensure data provenance, accessibility, and reuse across translational science
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application to medical imaging (e.g., MRI) · Experience with MRI data analysis, network science, graph theory, topological analysis, or related computational approaches, especially in Alzheimer’s
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real-world applications in green chemistry and industrial synthesis. Key Responsibilities: Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic
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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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include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval / Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date
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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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include: · building hierarchical causal graphs to account for the multi-scale structure of the experimental system, · detecting latent variables that may affect causal inference
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Information Modeling (BIM), including Revit, IFC, ifcopenshell, compliance checking, design generation, and design checking; and Experience in AI and LLM-related development, including RAG, knowledge graph
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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