Apply for an Academic Student Employee position

To apply for an Academic Student Employee position for a Data course, submit BOTH forms below:

  1.  ASE Application (required)
  2.  Fall 2023 ASE Supplemental Application for Data Courses (required)

Applications for Fall 2023 are closed.

Undergraduate applicants: Please note that EECS and Data undergraduate ASE positions are currently being negotiated by the ASE union and the university. Position titles, job descriptions, compensation structures, and numbers of positions are unknown at this time. The current application forms reflect the positions in the systemwide contract which is the default. We will provide further application information if the outcome of negotiations leads to changes in undergraduate positions. We hope that negotiations will conclude before the application deadline.

Data Course Staff Overview

The College of Computing, Data Science, and Society appoints graduate and undergraduate students to support its instructional programs. Our outstanding staff teams bear significant responsibility for our students’ experience and learning in Data classes. Staff team members also form strong bonds with each other, mentor junior members, and create staff networks for academic and professional development.

Course staff positions are Academic Intern (AI), Reader, Group Tutor, Undergraduate Student Instructor (UGSI), and Graduate Student Instructor (GSI). The last two titles are often jointly abbreviated as (U)GSI.

Academic Interns

Note: Academic Interns are not Academic Student Employees (ASEs). 

Academic Internship is a common starting point for staff in Data 8 and Data 100. Academic Intern positions require enrollment in a P/NP class, typically for 1 unit. Correspondingly, the expected time commitment is 3 hours per week on average. AIs do not receive financial compensation. Typical responsibilities consist of providing support for students in discussion sections, labs, or office hours, supervised by (U)GSIs. The primary selection criteria are motivation for teaching and overall academic performance including performance in the class. 

All the other course staff positions are Academic Student Employee (ASE) positions for which there is financial compensation. The table below provides a brief description of the typical responsibilities as well as campus requirements and salary scales.

Please note:

  • Detailed responsibilities for each position depend on the course and its instructors.
  • The number of AI and ASE positions in a course can vary across semesters depending on the budget, course enrollment, and course structure.
  • Undergraduate applicants who have no prior teaching experience are encouraged to consider AI, Reader, or Group Tutor positions before applying to be UGSIs.

What positions are available?


Typical Responsibilities

(Fall 2023)

Campus Requirements



Primarily responsible for grading and office hours.


Requirements for Readers

Salary for Readers

Group Tutor

Primarily responsible for academic support in small-group tutoring sessions.


Requirements for Group Tutors

Salary for Group Tutors

Graduate Student Instructor

Teaches discussion and lab sections; collaborates on diverse aspects of course execution. 


Requirements for UGSIs

Requirements for GSIs

Salary for GSIs

Typical Timeline and Process

  • ASE applications for the Summer and Fall are released in March or April. ASE applications for the Spring are released in October. Selection starts after the priority deadline for submission, but applications remain open for several weeks after that.

  • The application for Academic Interns for Fall semester is released in June or July, and the application for Spring semester is released in January.

  • Selection for ASE positions is a collaborative effort by the Faculty Director of Pedagogy, the course instructors, and relevant DSUS staff. Selection of AIs is a collaboration between the Faculty Director of Pedagogy, the course instructors, and some senior course staff.
  • Offers are made starting shortly after the priority deadline. The process can continue till the start of the semester of appointment, for example due to changes in appointees’ own plans.

Some Common Pathways

Berkeley offers a uniquely innovative set of undergraduate Data Science courses. 

Applicants for Graduate Student Instructor (GSI) positions who have neither taken nor taught the course for which they are applying should describe the background that qualifies them for the position. Qualified graduate students have priority over undergraduates.

Teaching is a skill that develops over years of experience. All Data course staff participate in regular meetings to discuss pedagogy and best practices. Undergraduate staff typically start as AIs or Tutors and later apply for positions of greater responsibility. Here are some paths commonly taken by undergraduates on our staff teams.

  • Data 8 and Data 100: A common progression is AI, then Tutor, then UGSI, with at least one semester as each of AI and Tutor. 

  • Data 140: The typical progression is Tutor, then UGSI, with at least one semester as Tutor.