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Field
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summarizing results, trends, and interpretation. Prepare visuals (graphs, micrographs, charts) for internal meetings and publications. 6. Collaboration and interdisciplinary communication Work in an
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engages in continuous professional development. Desirable criteria Experience of network analysis/graph theoretical techniques; Experience working with data related to mental health. Downloading a copy of
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fundamental research in physics-informed and symmetry-aware machine learning for nonadiabatic excited-state molecular dynamics. Develop and evaluate equivariant graph neural networks and related architectures
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parameters from parasite genetic data; cf., viral genomic epidemiology, where bifurcating trees capture the ancestry of DNA sequences, and human population genetics, where the ancestral recombination graph
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aerosols. - Visualization and post-processing tools: Proficiency in visualization tools (e.g., Python) and data post-processing tools to analyze simulation results and generate graphs, maps, and diagnostics
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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researchers in algebra, combinatorics and related disciplines, including finite geometry, algebraic graph theory, permutation group theory, coding theory and extremal combinatorics. The Centre offers a dynamic
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the images and extracted text, to generate and align with existing collection metadata Align entities with existing entities/records, including the objects themselves to bootstrap knowledge graph creation
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing
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fields: Agentic AI, Large Language Models, Artificial Intelligence, Biomedical Ontologies, Biomedical Knowledge Graphs, Computational Biology, Bioinformatics, Biomedical Informatics or a related field