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 Fall 2022 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, and 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 3-4:20p.m.) for part of the semester. AIs will also grade written student work, hold office hours, and answer students' questions online. 

Instructor: Daisy Huang
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 Daisy Huang with a resume/CV and their undergraduate and graduate transcripts as soon as possible.  Please copy Susan Johansen on the email.  Applications are accepted until all positions are filled.