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expensive and dangerous health threats, and responds when these arise. Research Project: This project will be across teams in the branch to provide an opportunity to learn about the needs of priority
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disease burden. Using these findings, you will learn to develop analytic approaches and research products that strengthen the Registry's ability to monitor ALS nationally and support evidence-based research
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to CDC's efforts to better understand the burden of CKD and inform public health strategies to improve prevention and outcomes. Learning Objectives: You will have the opportunity to advance your skills
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as safely and securely as possible. Learning Objectives: Under the guidance of a mentor, you will learn from DRSC’s Biosafety, Science, Training, and Expertise Branch while participating in a variety
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into scalable, high-performance code. Participants will have the opportunity to learn to apply and hone these skills and acquire additional ones as they work on real-world problems. Examples of Research Areas
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. Learning objectives include: Fractionation and purification of biomass into isolatable compounds for downstream development into products. Data organization and data management skills. Utilizing analytical
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learn and engage in research activities in several areas. These include, but are not limited to: Developing and testing MATLAB-based algorithms to assess brain injury risk from blast overpressure (BOP
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software and analytical tools. Gain exposure to specimen review, quality control, and laboratory data documentation practices used in molecular diagnostics. Learn quality management principles and practice
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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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of multiple surveillance and administrative data sources. Development of reproducible analytical workflows using programming languages such as R and Python. Application of machine learning and predictive