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summative evaluation plans and construct comprehensive logic models that capture program activities and outcomes. · Design evaluation procedures/protocols and develop data collection/survey
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summative evaluation plans and construct comprehensive logic models that capture program activities and outcomes. · Design evaluation procedures/protocols and develop data collection/survey
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on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage data collected from various sources, such as
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degeneration using knock-in models of inherited retinal diseases, and contributing to the development of novel therapeutic platforms. The successful candidate will conduct independent and collaborative research
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modeling, environmental simulations, and digital twin systems. -Develop analytical tools, visualization platforms, and decision-support dashboards to improve research outcomes. -Ensure data quality through
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sections on conceptual models, methodology, and significance. Collaborate with CARE leadership and project teams to prepare submissions to NIH, DoD, and private foundations. Develop an independent line
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using knock-in models of inherited retinal diseases, and contributing to the development of novel therapeutic platforms. The successful candidate will conduct independent and collaborative research
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will contribute to projects focused on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage
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students’ academic and mental health outcomes. Job responsibilities include: Conducting descriptive and advanced statistical analyses (including multilevel modeling) on extant and merged datasets using SAS
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and manipulating complex data structures, Bayesian modeling, analyzing nested longitudinal data, and who are familiar with techniques for handling challenging data (e.g., highly non-normal distributions