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results including recommendations for improving training. Learning Objectives: Under the guidance and training of a mentor you will be involved in several learning activities of the Division including
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activities, learning how to organize and synthesize information from diverse scientific programs. Under the guidance of a mentor you will perform a structured gap analysis to identify unmet research needs and
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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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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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scientists. Learning Objectives: You will learn a diversity of technical skillsets to develop, host, and maintain both internal and public-facing custom data solutions such as web-based applications, digital
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to multidisciplinary research aimed at advancing military medicine. What will I be doing? This opportunity offers a hands-on learning experience within a collaborative research environment focused on combat casualty
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presentations, technical reports, posters, abstracts, and manuscripts. Activities may be tailored your scientific background, interests, and professional development goals. Learning Objectives: During
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technology or Artificial Intelligence (AI) tools to solve business or administrative problems, demonstrated knowledge with Machine Learning (ML) and AI tools. Strong integration experience in enterprise
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and capability gaps. Learning Objectives: Through this opportunity, you will gain knowledge and practical experience in biosurveillance, emerging biological threats, public health preparedness, program
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watershed modeling Experience with analysis of geospatial data and time series data Experience with machine learning and statistical learning Experience with large, diverse datasets Familiarity with