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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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interferences. Method evaluation and validation – You may learn to prepare validation plans, assess performance characteristics such as accuracy, precision, analytical measurement range, limits of detection
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analytical technique. Build an understanding of pharmaceutical dissolution and drug-release principles and learn to evaluate relationships between formulation microstructure, chemical distribution, material
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, data engineering, data analytics, artificial intelligence, machine learning, deep learning, natural language processing, and automation using modern tools and techniques. During this fellowship, you will
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of a mentor, you will implement two-stage meta-analytic models and weighted least squares correlation methods to estimate the surrogacy strength of CGM-derived metrics (e.g., Time in Range (TIR
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unreported PFAS, contributing to enhanced food safety. Learning Objectives: Under the guidance of a mentor, you will learn to conduct research in the food safety arena, develop novel advanced analytical
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surveillance initiatives. Laboratory data-management skills: You will learn to operate various instrument software and a laboratory management database for analytical result review, laboratory information
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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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just medicines. Research Project: This educational research participation opportunity within FDA’s Office of Generic Drugs (OGD) provides a mentored learning experience focused on the evolving global
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, partnerships, data, analytics, and innovative technologies across CDC and partner organizations to strengthen the nation's ability to identify and understand emerging biological threats. Artificial intelligence