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regression models using Stata or R. Collecting, managing, and structuring quantitative datasets Conceptualization of suitable empirical methodologies and models Statistical analyses of complex datasets and
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programming, probability theory, and statistical analysis of large datasets using R or Python. A successful candidate should have a Ph.D. in Operations Research, Electrical Engineering, or Industrial
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working with large healthcare datasets (EHRs, claims, registries). Proficiency in R or Python. Strong quantitative skills and familiarity with advanced modeling techniques. Excellent written and verbal
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Substantial experience with Python Substantial experience with R The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be
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, or equivalent) Demonstrated experience with data analyses using Stata, SPSS, or R Effective oral and written communication skills Prior relevant publication in pediatrics research (minimum in press or under
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superb quantitative background, strong coding skills (e.g., Python, R), expertise in infectious disease modeling across multiple pathogens, expertise with large datasets and statistical analysis, and high
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, particularly in data analysis Experience with statistical analysis (e.g., SPSS, MATLAB) and programming (e.g., R, MATLAB, Python) Experience with fMRI data collection and analysis (e.g., FSL, SPM) Required
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skills in statistical software (e.g. R, Stata, Python) and working knowledge in SQL Excellent written and oral communication skills Strong record of distinguished scholarly achievement, including written
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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. Expertise in computational neuroscience software (e.g., MATLAB, Python) as well as statistical methods and statistical packages (e.g. SAS, R). Experience with machine learning methods is preferred