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(BDCL), within the Nutritional Biomarkers Branch (NBB), Division of Laboratory Sciences (DLS), National Center for Environmental Health (NCEH), develops and applies analytical methods for measuring
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translation, technical assistance, training and partnership development. For more information, visit: https://www.cdc.gov/nccdphp/dcpc/index.htm https://www.cdc.gov/comprehensive-cancer-control/about/index.html
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scientific considerations that may influence generic drug quality, access, development pathways, and approval timelines across jurisdictions. You will engage in interdisciplinary research and training
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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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and analyze trait measurements related to plant development, plant physiology, and seed yield under different irrigation regimes in two locations with different weather patterns. You will also aid in
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, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural
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ranges and glycemic variability measures, develop or adapt missing data methods for count-based or overdispersed discrete endpoints such as hypoglycemia event rates, and incorporate hierarchical and
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ingredients (excipients) present in FDA-approved drug products, supporting both drug development and regulatory processes. This opportunity will provide you with hands-on exposure to the operational and
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genomics, and pathogen discovery. The fellowship will focus on the development, evaluation, and application of advanced laboratory and sequencing approaches for the detection and characterization of known
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend