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scalable modeling framework. The primary focus of this appointment is to provide hands-on training in data synthesis, uncertainty evaluation, and predictive modeling while contributing to foundational
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collaboration within the Federal Statistical System network, adopting a common framework for protecting statistical data, and disseminating statistical data securely and equitably, in accordance with
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) subseasonal-to-seasonal (GEOS-S2S) prediction system using MOM6, CICE6, and JEDI/SOCA. Continuing sea ice development within the GEOS-S2S framework seeks to improve process understanding and substantially
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) Familiarity with mathematical programming solvers (e.g., Gurobi, CPLEX) or probabilistic/Bayesian computing frameworks (e.g., Stan, PyMC) Ability to formulate high-impact, novel and well-defined research
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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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scientific insights into structured, prioritized research recommendations. Deepen understanding of research-priority frameworks used within federal public health agencies. Strengthen scientific communication
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emerging events; research biology-related AI capabilities and their implications for biosecurity; and contribute to frameworks for responsible evaluation and use of AI, including scientific validity
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-based curricula, educational materials, and assessment strategies. Develop skills in instructional curriculum and design through application of adult-learning principles, instructional design frameworks
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engage in research and evaluation projects under the guidance of experienced mentors, applying implementation science frameworks to assess cancer prevention, screening, and survivorship interventions
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potential public health impacts of chemical exposures. Learn ATSDR methods and frameworks for conducting environmental public health assessments and risk evaluations. Gain experience creating data