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? GPH-GU 2182 Statistical Programming in R (Graduate) Department: NYU School of Global Public Health - Biostatistics Supervisor: Dr. Rebecca Betensky Employment Dates: Fall 2025 R is one of the most
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) - Strong computational, statistical, and technical skills (e.g. fluency with Matlab, Python, and/or R) - Experience analyzing neuroimaging data (SPM, FSL, AFNI, or similar platforms) Candidates should submit
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Experience Candidates would be familiar with statistics and econometrics. Experience with some of the relevant software to conduct statistical analysis (e.g., Excel, R, STATA). Previous research assistantship
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derivation, and applications are demonstrated using common statistical software, Stata and R. Compensation depends on level of experience. Multiple sections are available: Mondays: 4:55?6:35pm (Lecture); 6:45
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). Proficiency in data analysis software such as R, SPSS, STATA, etc. is preferred. Capable of developing effective relationships with faculty, students, academic administrators and external visitors or parties
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preferred. Proficiency in computational tools such as MATLAB, Python, R, or machine learning applications in immunology is desired. Candidates should have a PhD in Chemistry, Chemical Engineering
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is preferred. Proficiency in computational tools such as MATLAB, Python, R, or machine learning applications in immunology is desired. Salary range In compliance with NYC?s Pay Transparency Act, the
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Qualifications being sought are (1) coding fluency in R and Bash and (2) working knowledge of Python. In addition, experience performing experiments with budding yeast (S. cerevisiae) is required. Those interested
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Compliance, SNAP-R, AES etc.) Qualifications In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is USD $142,000.00 to USD $182,000.00. New York University considers
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sets in Excel, Stata, Matlab, R, or similar software Exceptional academic record Excellent attention to detail Strong interest in economic development in emerging markets Excellent written and verbal