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computing (HPC) environments and include data assimilation techniques in a Bayesian framework. Under the guidance of a mentor, the participant will identify and integrate multiple data streams into the model
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formulations to target multiple pathogens. The technology uses a genetic blueprint to create a novel mRNA for target proteins, which can be encapsulated into lipid nanoparticles (LNPS) for delivery and cellular
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received by November 1, 2025. Preferred skills: Demonstrated experience in modeling and applied statistics including machine learning, Bayesian statistics, multivariate statistics, model assisted estimation
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through innovations in the food and nutrition environment. RAFSRU conducts targeted research on human health and nutrition across all life stages, generating fundamental knowledge on the interplay among
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mentor, the participant will conduct research on targeted and non-targeted analysis of per- and polyfluoroalkyl substances (PFAS) in food and food contact materials. The participant will be a part of
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theoretical formulation and analysis to testing algorithms in real-time on representative target hardware or in system-in-the-loop environments. This Post-Doc position will support the development and
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are available during specified periods in order to conduct experiments and 2) conduct field experiments to delineate host association of egg parasitoids and impact on emerald parasitoids and other non-target
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insects from abroad are imported and evaluated for both the safety (non-target risk) and efficiency of candidate biological control agents against target pests. By carefully evaluating, selecting, and
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cGMP conditions, microsatellite analysis, targeted sequencing, SNP analysis and WGS analysis. This combination of assays is extremely difficult to find. Furthermore, you will be conducting analyses using
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will receive hands-on training and mentorship while contributing to high-impact studies that combine cell-based systems, transgenic/gene-targeted mouse models, and natural hosts (cattle, deer, and sheep