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Adjunct Instructor - GPH-GU 2182 Statistical Programming in R (Graduate)

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New York University

New York University, New York, NY, USA

5 Star Employer Ranking

Adjunct Instructor - GPH-GU 2182 Statistical Programming in R (Graduate)

Position: Adjunct Instructor – 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 popular programming languages in statistics and data science. This course will introduce various R programming topics, including R objects, data visualization, data import & export, data manipulation, creating functions and iterations for statistical simulations, and writing high-quality reports with R Markdown. The course will focus on public health datasets as illustrations to best meet the practical needs of GPH students but is also open to those of other backgrounds. By the end of the course, students will be able to comfortably program in R for effective data preprocessing, analysis and presentation. This course does not require prior experience in programming or statistics and serves as a foundation for other courses in biostatistics, epidemiology, and data science.

Two sections are available:

  • Wednesdays, 2:00–4:40pm, Sept 3 – Dec 10, 2025
  • Mondays, 4:55–7:35pm, Sept 8 – Dec 8, 2025

Qualified applicants will have an advanced degree in statistics or a related field (PhD preferred). Previous experience teaching introductory statistics is preferred.

If interested, please upload a CV and cover letter via interfolio.

In compliance with NYC’s Pay Transparency Act, the hourly rate for this position is $222.27. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate’s work experience, education/training, key skills, internal peer equity, as well as market and organizational considerations when extending an offer.

For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr

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