Princeton University

Center for Statistics and Machine Learning - SML 201 AI

The Center for Statistics and Machine Learning at Princeton University has openings for AIs to teach precepts for SML 201: Introduction to Data Science during the Spring 2025 semester. The course covers approaches and techniques for obtaining, organizing, exploring, and analyzing data. The material covered also includes predictive modeling, R programming for data science, and the basics of statistical inference (random variables, sampling, probability distributions, parameter estimation, hypothesis testing, cross-validation, and penalized and unpenalized linear regression.)

AIs are required to lead an 80-minute precept for the entire semester and to attend two weekly course lectures (either Tu/Th 11a.m.-12:20p.m. or 1:30-2:50p.m.) for part of the semester. AIs will also grade written student work, hold office hours, and answer students' questions online. To be qualified, the candidate must be a registered Princeton graduate student for the semester that they work.  

Instructor: Derek Sollberger, Day Yi
Appointment per precept: 3 hours
Requirements: Background in statistics and programming. Enthusiasm for teaching beginners. Proficiency in R is an asset. We welcome applications from students in both technical disciplines and the candidates working with data in the social sciences.

Interested candidates should contact Derek Sollberger and Day Yi.  Please attach a resume/CV and both undergraduate and graduate unofficial transcripts.  Please copy Susan Johansen on the email.  Applications are accepted until all positions are filled.