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or gene editing by CRISPR-Cas9 is required. Experience with flow cytometry and/or mass cytometry analysis is desirable. Interest in learning new technologies is mandatory. Basic R programming skills
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. Proficiency in programming (e.g., Python, R) and familiarity with common bioinformatics tools and packages. A PhD in developmental biology, cell biology, regenerative medicine, or a related field. A required
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technical skills in statistics, data science and psychometrics Experience with open-source software development (or high proficiency) in R or Python Domain knowledge in reading development, dyslexia research
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an individual with strong statistical and computing backgrounds. Successful applicants should have a Ph.D. degree in epidemiology (or biostatistics or a related field). Strong programming skills in R are required
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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. Record of peer-reviewed publications. Knowledge in one or more of the following areas is
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, proficiency in R and at least one additional scripting language (e.g., Python) and knowledge in biostatistics are required. Experience working with genetic association studies, immune repertoire, single cell
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction
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. Candidates should also demonstrate strong skills in Python (for ML/NLP tasks) and R (for statistical modeling or data analysis), as both will be actively used in the research workflow. Importantly
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proficiency in R, Python, Stata, or SAS. Demonstrated experience with large administrative or EHR datasets; experience with Medicare or Medicaid claims strongly preferred. Excellent written and verbal
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is preferred. Familiarity with psychological concepts and/or experience with human subject data is preferred. Profound experience in statistical and computational approaches. Experience with R