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University is recruiting postdoctoral scholars with prior training in statistics, biostatistics, computer science, bioinformatics or a closely related area. Applications are invited from ambitious, independent
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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics. Strong
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analysis skills, with a minimum of 3 years of statistical programming experience with R (possibly also Stata, Python or other statistical software) Excellent oral and written English-language communication
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is a plus. 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
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Qualifications: PhD with substantial expertise in data science, geospatial techniques, and statistical/causal inference Required Application Materials: CV 1-page cover letter describing research background and
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documentation. Select appropriate statistical tools for addressing a given research question. Conduct and interpret statistical analyses including regression, survival, and longitudinal models. Implement data
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to develop Linux-based scripts, program in Python, use of GitHub. Experience with medical imaging datasets. Experience with basic statistics for health sciences. Experience with AI software frameworks
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required. Duties include: Design studies. Develop and implement protocols for quality control. Create analytic files with detailed documentation. Select appropriate statistical tools for addressing a given
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required. Duties include: Design studies. Develop and implement protocols for quality control. Create analytic files with detailed documentation. Select appropriate statistical tools for addressing a given
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these to children, adults, and their families at local and global levels. Transforming lives with innovative science and compassionate care. Duties include: Create complex charts and databases, perform statistical