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(ML), to help solve complex agricultural problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis
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(RVFV). With mentor guidance, you will plan and execute complex experiments to study viral replication, pathogenesis, and transmission dynamics. Using a multidisciplinary approach, you will use or enhance
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organizing and completing complex tasks. Proficiency in Office 365 Suite of Products: Outlook; TEAMS; SharePoint Ability to use Microsoft Teams for communication Experience with website design and user
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research priorities. Additionally, you will learn to synthesize complex scientific findings into technical evaluations, author peer-reviewed manuscripts, and develop empirical data visualizations
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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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development Ability to analyze complex datasets, identify trends, and effectively communicate findings to technical and nontechnical audiences Interest in applying data science and technology to public health
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understanding of micro- and nanoplastics (MNPs) as well as risk assessment. You will gain experience engaging with complex scientific information from a variety of disciplines related to MNPS, as well as data
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journals Experience in microbiology and fermentation Show independent initiative, effectively troubleshoot complex biological systems, and communicate ideas clearly in group settings Point of Contact Janeen
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dynamics of complex human and natural Earth-system interactions and to deliver actionable intelligence at scales and timeframes relevant to decision makers. As the Nation's largest water, earth, and
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pathogen infection, including newly discovered agents, on bee physiology and colony health. Analyze complex biological datasets and communicate findings through presentations and peer-reviewed manuscripts