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predictive modeling, to identify distinct phenotypes of diabetes and characterize factors associated with disease onset, progression, complications, and mortality. Gain experience analyzing administrative
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: The appointment is full-time. Participant Stipend: Stipend rates may vary based on numerous factors, including opportunity, location, education, and experience. If you are interviewed, you can inquire about the
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, remote sensing, numerical modeling, and data science within an applied research environment. Engage with an interdisciplinary scientific team and interagency collaborators, strengthening professional
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rates may vary based on numerous factors, including opportunity, location, education, and experience. If you are interviewed, you can inquire about the exact stipend rate at that time and if selected
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data collection with quantitative statistical and modeling analyses and are collaborations with natural resource managers, veterinarians, and academics. You will learn to develop and conduct research
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managing diabetes using computer simulation models. Learning Objectives: You will learn: How to synthesize and translate empirical evidence on cost-effectiveness of interventions for the prevention and
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tools to support current business processes. Gain experience gathering software and systems requirements. Learn data modeling, data mapping, and data transformation. Train in developing reports utilizing
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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
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, COMPASS-31 measures, etc. The project may include descriptive analysis, multivariable modeling, and integration of findings across epidemiologic datasets to improve understanding of infection-associated
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modeling techniques to identify patterns, trends, and emerging public health concerns. Design and evaluation of interactive data visualizations and dashboards to communicate scientific findings. Best