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: Develop multiscale ABMs of multi-cellular immune cell populations and virus interactions. Design, implement, analyze, and validate agent-based, ODE, PDE, stochastic, hybrid, or surrogate models, selecting
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the mechanisms of, and interventions for, immuno-senescence and aging in lung transplantation using high-throughput multi-‘omic approaches, primary cell culture systems, and animal models of transplantation. Ph.D
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in AI for genomics (e.g., generative models, transformers, genomic language models, agentic AI) and related areas of statistics (e.g., uncertainty quantification for machine learning and AI). Apply
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell