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mental health and computational social science, using large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data
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expertise in Large Language Models (LLMs), Agentic Systems, as well as strong interdisciplinary teamwork skills and communication skills. About the Stanford NLP Group: Stanford NLP Group focuses on basic
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or orthotopic tumour models Supporting preclinical treatment studies involving standard-of-care or experimental agents Applying in vivo imaging techniques (e.g., bioluminescence imaging) to monitor tumour
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research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems for viral agents. Emphasis is placed on determining
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. Desirable criteria Track record of interdisciplinary collaboration. Familiarity with cognitive architectures or agent-based modelling frameworks. Ability or potential to contribute to the development
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Framework (RDF). enables advanced data mining queries using the SPARQL query language. provides a natural language-based interface to perform these queries on the knowledge graph using a large language model
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, a spatially-explicit agent-based model of land use change in Great Britain. This will be coupled with a system dynamics model of macro-scale drivers of land system change. Working with colleagues from
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
, designing natural language interfaces for more intuitive navigation of the BDC environment, creating BDC-specific foundation models, and enabling large language models (LLM) and machine learning-based