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approaches. Experience in programming in R, using GitHub, and doing Bayesian statistical analyses with the use of MCMC samplers such as JAGS, STAN, or NIMBLE. Point of Contact Justina Eligibility Requirements
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use of molecular assays such as real-time PCR and next-generation sequencing to study the prevalence of infectious diseases in the target study populations. Learning about sample testing under a
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skills: Demonstrated experience in modeling and applied statistics including machine learning, Bayesian statistics, multivariate statistics, model assisted estimation, rarefaction, or wildland fire
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to identify formations with existing wells that could be targeted for laproscopic critical mineral extraction is an active research focus of NETL. This project will be focused on the direct examination
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TSCAN network data), 2) to create tools that address identified needs, and 3) to provide education and outreach around the use and value of existing and new tools. Two audiences will be targeted in
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that should be targeted in restoration and land treatment practices. Second, managers need to know how changes to vegetation structure, driven by disturbances and/or vegetation treatments, influences a
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in several areas. These include, but are not limited to, Using MPS to identify new potential targets for future medical countermeasure development Learning development and characterization
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Objectives: Learn about and participate in Ohia plant propagation and develop targeted studies to increase silviculture capacity. Learn greenhouse, nursery and field operations for developing a disease
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for health diagnostics and continuous monitoring. Current areas of interest for the project are recognition element integration, microfluidics, circuit design and computer interfacing. This project targets
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grammar & machine learning for inverse-designing polymers with targeted thermo-mechanical properties by tuning the polymer chemistry & architecture, catering to Artic & Space applications. The framework