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and oligonucleotide therapeutics (ONTs), through the integration of nonclinical safety data evaluation and Model-Informed Drug Development (MIDD) approaches. Under the guidance of a mentor, you will
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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
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partners. You will analyze complex datasets, develop and document analytical methods, and contribute findings to policy-relevant outputs. This will include relational databases such as SQL and PostgreSQL
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health threats, and responds when these arise. Research Project: The DPS leverages partnerships to support CDC in developing the capacity of the public health system and state, tribal, local, and
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to develop genetic, genomic and molecular resources for for supporting the barley and oat research. Research Project: You will be involved with one of the two research projects: I. Barley genetics and
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the development of new and enhanced technologies that support vegetable pickling, by fermentation or acidification, in the USA, under the USDA-ARS National Program 306, Quality and Utilization of Agricultural
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surveillance activities across participating sites, support data collection and data quality efforts, develop and maintain surveillance tools and guidance, and facilitate communication and collaboration across
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USDA-ARS Molecular Biology Postdoctoral Fellowship in the Natural Products Utilization Research Unit
Unit develops natural products for use in agriculture, producing more toxicologically and environmentally benign pest management tools and improving the value of crops. A secondary mission is to conduct
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: Research will be focused on the development of bioinformatic and genomics tools
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managements affect crop yields, soil organic carbon and nitrogen, plant nutrients uptake and soil pH. Also, gaining experience in using process-based models or developing digital twins for the soil carbon and