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Instructional Assistantships at Computational Social Science

Thanks for your interest in serving as a graduate IA (TA) or reader for Computational Social Science at UC San Diego!

We get many more requests for IAships than we have spaces for students, so this site is designed to help you and your advisor determine whether you're a good fit to IA in our program. 

Note that although we hire both 'readers' and graduate IAs, the text below pertains to both where not specified. We typically have one to three instructional grad opportunities per quarter.

Required Skills and Qualifications

To be considered for an position in CSS, you must have:

  • At least moderate familiarity with Python and ability to write and evaluate basic programs
  • At least moderate familiarity with NumPy/Pandas/MatPlotLib for data analysis
  • Strong understanding of methods and problems in cleaning and tidying datasets
  • At least moderate familiarity with inferential statistics (e.g. understanding the process and purpose of linear/logistic/mixed regression)
  • Experience with quantitative data analysis (whether 'big data' or (e.g.) from experimental work)
  • Status as a current or recently graduated (for summer) UC San Diego graduate student
  • Ability to work in the US during the quarter in question
  • Ability to be on campus in San Diego during the quarter in question
  • All students must be classified as 'native speakers' or complete certification showing requisite language proficiency per GEPA policy
  • All students must be in 'good academic standing' as defined by GEPA policy
  • Home department approval to serve as an IA in our program
  • A genuine desire to teach and help our students

Preferred Skills and Qualifications

All other things being equal, we will give preference to candidates who have any or all of the following:

  • At least moderate understanding of machine learning (e.g. concepts like classification, clustering, training vs. testing, overfitting, ROC/AUC, etc.)
  • At least moderate familiarity with R, Julia, MATLAB, or another statistical programming/scripting language
  • At least moderate familiarity with concepts in Neural Network Machine Learning models (e.g. Transformers, backpropagation, convolutions, LLMs)
  • Participation in a departmental IA training program (please describe in your application!)
  • Participation in 'Introduction to College Teaching' offered through the Teaching and Learning Commons at UC San Diego
  • Instructor recommendation from a prior quarter teaching in a CSS class
  • Ongoing research which is clearly aligned with the class goals
  • Prior completion (with good grades) of the class or program in question
  • Recommendation from a CSS Affiliated Professor

Order of Priority for IA Selection

Because we have so few slots available, we must choose our candidates carefully, and part of this process involves prioritizing our slots for folks in our program, participating departments, and school.  So, in order of descending priority, we would prefer to hire as IAs…

  • Previously hired IAs from CSS classes (with instructor recommendation)
  • CSS Ph.D. Specialization Students
  • Ph.D. Students from departments in the School of Social Sciences
  • Ph.D. Students in related fields in other Schools (e.g. Engineering, HDSI, Rady)
  • Masters Students from the UCSD CSS Program
  • Masters Students from within the School of Social Sciences
  • Ph.D. Students who are outside their departmental 'guaranteed support' timeline
  • Masters Students in related fields in other Schools (e.g. Engineering, HDSI, Rady)

If you accept a TA position during a quarter and later decide to decline for non extenuating circumstances, you may lose priority for CSS TA positions in future quarters.

This is a 'rough guide' we will use, rather than a hard-and-fast rule, and students who are low in this ranking could rise to the top due to exceptional experience, skills, recommendation, or program need. Please feel free to apply even if you're not at the top of the rankings, however, it is important to be aware that a suitable position may not be available.


Compensation will be consistent with the UCSD Union Contract Agreement in force during the quarter of teaching. 

Duties and Responsibilities (Graduate IAs)

Specific responsibilities will vary from class to class and instructor to instructor, and will be detailed on a per-class basis in the IA Description of Duties.

Within our program, IAs often lead discussion sections, tutorials, or lab sessions, complementing the primary lectures delivered by professors. They are also often responsible for grading assignments, quizzes, and exams, providing timely feedback to students. IAs also hold office hours, offering individualized assistance to students, clarifying course material, and addressing academic concerns. In some cases, particularly with experienced IAs who would like more teaching experience, IAs may be given the opportunity to assist in designing course materials, developing lesson plans, or offering guest lectures.

IAs are expected to be present and available to help and accomplish their duties from the start of preparation of the quarter until final grades are submitted, and should contact the instructor in the event that any scheduling conflicts arise, to either find short-term coverage, or in the event of a substantial and good-cause difficulty interfering with teaching, to identify a replacement IA.

Additionally, IAs should attend their designated office hours and sections. If a TA cannot make it due to sickness or other commitments, they must inform the course instructor to explore the option of a substitute. Additionally, TAs should promptly inform their students of any changes or cancellations to their regular discussion sessions or office hours.

Duties and Responsibilities (Readers)

Specific responsibilities will vary from class to class and instructor to instructor, and will be detailed on a per-class basis in the Reader Description of Duties.  However, designated 'Readers' are expected only to help with grading and evaluation of papers and assignments, with no in-person or one-on-one with student components.

Confidentiality and Privacy

All information related to individual students, including completed assignments, exams, grades, and correspondence, must remain confidential from anybody outside the instructional team (including parents of students) unless the student provides written permission. More specifically:

  • IAs should never grant students or third parties access to their computer, canvas accounts, or files.
  • Posting grades using names or any identifiable numbers, such as a PID, student ID, or social security number, is prohibited.
  • Publicly distributing graded assignments (e.g 'grab your graded exam from the stack on the front desk' rather than handing individual exams to corresponding students) is not permissible.
  • Keys, solutions, and exam materials should be securely stored and shared with nobody
  • IAs should follow all relevant state and federal laws (e.g. FERPA) on student data confidentiality

Abuse of Authority

It's essential for IAs to act professionally and avoid misusing their power. They should assess students' work impartially and justly, without regard to the student who submitted the work. Here are a few among the many kinds of abuse of authority which will not be tolerated:

  • IAs are prohibited from serving as paid 'Tutors' for the course as they are teaching it, as this will necessarily result in (perceived or actual) favoritism towards paying students
  • IAs are prohibited from having any romantic or sexual relationship with a student, as doing so is not only ethically wrong, but considered misconduct by the university.
  • IAs must not accept or solicit bribes or any other type of quid pro quo offers in exchange for grades, grade changes, extra credit, or other assistance with the class, and must immediately disclose any offers made by students to the instructor.
  • IAs must disclose to the instructor any pre-existing relationships with students in the class (e.g. friends, (ex) partners, co-workers), and are prohibited from grading or evaluating that person's work or making changes to that person's grades, attendance, or otherwise

More generally, IAs should be mindful of the power gradient which exists between them and students, and consider their words and actions carefully, as even an offhand negative comment (e.g. 'Well, that was stupid, want to try again?') or joke (e.g. 'You can't answer that? That's it, you fail the class!') can have serious effects on student anxiety and mental health. Kindness is always correct.

Authoritative Document

Although we believe these guidelines are consistent with both the letter and spirit of the UC and UAW Union Contract Agreement, the contract agreement is the authoritative document for any questions about the differences between this document and the Union Contract Agreement.

How to Apply

If you're interested in becoming a graduate IA for CSS, please use the online UC San Diego IA Application Portal. The application opens for the quarter when the schedule of classes is released. 


Thank you to the UC San Diego Computer Science & Engineering Department, on whose helpful website ( some of the above language is based.