Position ID: | Cornell-Statistics and Data Science-VAP [#23784] |
Position Title: | Visiting Assistant Professor |
Position Type: | Non tenure-track faculty |
Position Location: | Ithaca, New York 14853, United States [map] |
Subject Area: | Statistics / Data Science |
Appl Deadline: | 2022/11/28 11:59PM* finished (2022/11/18, finished 2023/06/03, listed until 2022/11/28) |
Position Description: |
The Department of Statistics and Data Science seeks applicants to fill a position at the rank of Visiting Assistant Professor (VAP), to begin Fall 2023. This VAP will teach on campus courses and develop online course material in the Professional Masters in Applied Statistics & Data Science and Undergraduate programs with an emphasis in data science, statistics, R programming and machine learning. Teaching responsibilities, general duties include holding office hours, developing syllabi, assignments, writing and grading exams, supervising teaching assistants, and maintaining a course website. Other duties may be assigned by the chair as necessary. The initial appointments are for a term of three years, with contract renewal contingent upon satisfactory performance.
Preference will be given to applicants with prior experience of developing course materials (videos, quizzes etc.) suitable for building active learning initiatives in virtual and in-person classrooms. The ideal candidate will assist in the development of online introductory statistics content. The successful applicants will be fluent in advanced data wrangling techniques in R and be prepared to teach and develop data science courses including advanced graphics, statistical methods, regression, statistical learning, data mining and machine learning.
The ideal candidate will assist in the development of online data science degree programs. Additional responsibilities may include coordinating multi-section courses, supervising teaching assistants, serving on committees, supporting growth in the university’s data science degree offerings, and advising data science students at the undergraduate and masters levels. A PhD in statistics, applied mathematics, or related field is required.
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