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Field
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analytical methods for the analysis of linked data from electronic health records and genomic or molecular sources. Strong statistical skills (e.g. proficiency in R or Stata), along with excellent writing
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interpersonal, communication, organizational, problem-solving, and statistical software skills (e.g., R). Strong background in quantitative data analysis and research methodology is preferred. Ideal candidates
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reports and contributing to scientific publications. Strong verbal and written communication skills for presenting experimental findings. Additional Considerations: Previous experience working in an R&D
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written communication skills for presenting experimental findings. Additional Considerations: Previous experience working in an R&D or academic research environment. Experience with safety protocols
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software packages (e.g., SPSS, R). Other Requirements Ability to work independently and as part of a team. Analytical skills and the ability to resolve technical or research problems and issues and to
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, immunology, high dimensional omics analysis, or mass spectrometry. • Strong data analysis skills using R, Python, or equivalent. • Excellent verbal and written communication skills. • Ability to work both
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to: Be trained to work on the collaborative PLAY study. Work on coding and collating the dataset including coding using the R program language for data cleaning and analysis. Organize lab meetings and
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optimization. • Proficiency in programming (Python, R, Julia, or similar) and experience with frameworks like PyTorch, TensorFlow, or JAX. • Prior research in statistical learning and online optimization
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collect data in the field. Additional duties include, but are not limited to: Be trained to work on the collaborative PLAY study. Work on coding and collating the dataset including coding using the R
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, SAS, R, Stata, and relational database (e.g., SQL) tools Experience with statistical analysis in applications such as SPSS, SAS, R, and Stata using syntax/command files, macros in SPSS, SAS, and/or