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, overlap, and opportunities for integration; explore methods for measuring development and performance; analyze how clinical, laboratory, genomic, environmental, event-based, and other surveillance
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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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, 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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learning methods for process automation within SharePoint and Microsoft enterprise platforms. Under the guidance of a mentor, the participant will explore research approaches related to large language model
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science methods for improving public engagement, the National Environmental Policy Act (NEPA) and associated environmental analyses, offshore energy policy, approaches to bringing innovation into government
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analytical methods in the R programming language. Stipend $85,000.00 – $95,000.00 Yearly Point of Contact Rachel Eligibility Requirements Degree: Doctoral Degree. Discipline(s): Computer, Information, and Data
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. Training activities will include analyzing existing datasets and generating new molecular and metabolic data using advanced sequencing technologies and bioinformatics methods. Throughout the project, you
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systematic literature review, study design, and analysis of environmental health and exposure data while gaining experience applying epidemiologic, exposure-assessment, and biostatistical methods relevant