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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
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) and healthy controls, funded by a NIH NIGMS ESI-MIRA (R35) (https://anesthesiology.duke.edu/news/nih-grant-awarded-explore-microbial-influence-sepsis) . This position is ideal for a highly organized
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characterizing the endocrine-disrupting potential of plastic additives, with a primary emphasis on androgen receptor (AR) and estrogen receptor alpha (ERα) modulation, using established in vitro and in vivo models
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neurobiology, RNA biology, and evolution. We are especially interested in understanding: How does post-transcriptional control shape neural cell fate and disease? We have discovered canonical and non-canonical
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advanced epidemiologic and biostatistical methods, including causal inference, survival and longitudinal modeling, and approaches for integrating multi-level and high-dimensional data. There will be
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induce more protective immune responses in the non-human primate (NHP) model by exploring innovative mRNA constructs for immunogen delivery that can elicit both protective and therapeutic B and T cell
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-throughput genomic screening approaches, primary cell culture systems, and animal models of influenza disease. For more information visit https://mgm.duke.edu/faculty-and-research/primary-faculty/nicholas