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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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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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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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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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.) and proficiency in data analysis software (such as R, Mplus, SPSS). Extensive experience interpreting research data and summarizing findings via written reports and oral presentations. Strong record
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phenotyping, sequencing, gene editing, and the isolation and characterization of extracellular vesicles is desired. Proficiency in bioinformatics tools and programming languages (e.g., R, Python) for data
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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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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
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statistical programming. Strong programming skills in R are required. Required Application Materials: A cover letter, CV, a short description of research interests, and contact information of three referees
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Qualifications: • Doctoral degree with quantitative training (ideally in econometrics) or relevant research experience. • Strong coding skills in R, Stata, or other statistical software package. • Good