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We are seeking a postdoctoral researcher with a focus on developing statistical, machine learning, and causal inferential methods with applications in health care. The postdoc will collaborate
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, mixed methods, or implementation science) • Experience with quantitative or qualitative data management and analyses using statistical software (eg, SAS, R, NVivo) • Excellence in communicating research
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. The position includes training and consultation with supervisors, a potential for provision of direct clinical service to participants enrolled in trials, data management and statistical analysis, manuscript and
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management skills (we prefer experience in R) and a strong background in statistical analysis, economics, and/or and machine learning. Ideally, this candidate will be proficient in causal inference and
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with strong data analysis and management skills and a strong background in statistical analysis (especially time-series analysis), causal inference, advanced econometrics, and/or machine learning
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, expertise with large datasets and statistical analysis, and high level of independence with publication record to support these characteristics. The postdoctoral scholar may work alongside students in
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conducting standardized diagnostic interviews • Comfort with working with children and their families • Familiarity with statistical analysis softwares • Knowledge of nutrition and food science. PHYSICAL
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infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high level of independence with publication record to support these characteristics
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sciences, or advanced numerical methods, especially in assessing algorithmic complexity/scaling; • Experience using machine learning, statistical analysis, and optimization. • Experience in modeling and
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, data acquisition, data processing, statistical computation, methods development, data interpretation, literature review and manuscript/grant preparation. Additional Duties: Supervision of undergraduates