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to complement your education and support your academic and professional goals. Along the way, you will engage in learning activities and research in several areas. These include, but are not limited to: Assess
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) framework to assess biological risks associated with blast overpressure (BOP) from military weapon systems. You will engage in research and applied computational activities to model blast-induced energy
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scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning
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environmental factors associated with CKD incidence and trends. Apply advanced statistical and machine learning methods, including semi-supervised cluster analysis, to characterize populations with diabetes and
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reports/visualizations and presentations, and collaborating with multidisciplinary teams. Learning Objectives: You will train with CDC’s Center for Forecasting and Outbreak Analytics, gaining hands
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domestically and globally. Fellowship activities are organized across three interconnected project areas, each offering structured training and learning experiences. Project 1: Drug Competition and Access You
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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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enhance assignment allocation and improve the efficiency and consistency of pharmaceutical quality assessments. Learning Objectives: You will gain experience in data analysis, algorithm development, and the
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-clinical and pre- and post-market clinical data. Learning Objectives: You will conduct research under the mentor’s guidance but will also have the opportunity of demonstrating your skills of acting
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. Additional Desired Qualifications: Demonstrated success in collaborative environments. Experience with NASA remote sensing data and machine learning. Experience communicating scientific concepts to wide