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the network. You will also participate in the analysis and interpretation of respiratory virus hospitalization surveillance data, including applying epidemiologic and statistical methods, developing
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systems. Activities may include collecting and analyzing experimental data; utilizing advanced optical diagnostic methods, high-speed imaging systems, and engineering instrumentation to characterize
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Objectives: Build competency in designing and planning science studies, including performance measurement and mixed-methods data collection. Strengthen skills in applying quantitative and qualitative analysis
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, gaining exposure to public health research, evaluation, and scientific operations that support agency priorities. The participant will strengthen skills in epidemiologic methods, scientific literature
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Microsoft Office applications and familiarity with statistical analysis methods and software. Critical thinking and scientific judgment to evaluate complex environmental health data and site conditions to
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physical activity promotion. Learn how to apply quantitative and qualitative analytic methods, including opportunities to use GIS, statistical software (R or Python), and emerging analytic approaches
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wildlife. Use molecular techniques, including CRISPR-based methods and cloning, for vaccine and diagnostic development. Describe microbiological, pathological, and immunological approaches used to study
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of several scientists, you will gain exposure to field and laboratory methods used to understand soil-plant-water interactions, crop needs, and conservation processes. Specific learning activities include
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., Medicare and Medicaid) to examine clinical and environmental factors associated with CKD incidence and trends. Apply advanced statistical and machine learning methods, including semi-supervised cluster
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machine learning methods, including cluster analysis and predictive modeling, to identify distinct phenotypes of diabetes and characterize factors associated with disease onset, progression, complications