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nutrition Experience in data processing, statistical analysis, and interpretation of data Ability to develop crop nutrition aspects of team field experiments Point of Contact Sara Beth Eligibility
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, and presentations. Gain exposure to innovative tools and practices and develop skills in partnership mapping and leveraging artificial intelligence to support evaluation, data analysis, and
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health Behavioral science Health communication Behavioral theory Qualitative data analysis Quantitative data analysis Evaluation Point of Contact Rachel Eligibility Requirements Citizenship: U.S. Citizen
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GPS, a downward-facing camera, and onboard machine learning capabilities for coastal sediment imaging and analysis. The experience will also provide an in-depth introduction to the Robotic Operating
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months. Preferred Skills: A background in computer and/or data science with some experience in machine learning, multivariate statistical analysis, artificial intelligence, or computer programming. Some
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AIV infection. Learning Objectives: You will learn methods for analysis of plasma-based biomarkers of avian health and will gain experience with analysis of samples and the collected data. You will also
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for developing and using systems to phenotype root systems in greenhouse and field settings under the guidance of research mentors. Build skills in root image processing and other data analysis activities using
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, scour-resistant features, and flood-risk-mitigation designs, building a broader appreciation for how computational methods support analysis of real-world hydraulic challenges. Along the way, you can
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for data analysis and interpretation. You will be integrated into a transdisciplinary research team and engaged in multiple aspects of project planning, communication and coordination, research
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sequencing (eWGS), PCR-based HPV genotyping platforms such as Novaplex HPV28, and data analysis approaches used to support reliable HPV surveillance and vaccine impact monitoring. This research aligns with