Our two-year M.A. program draws on some of the latest innovations in machine learning, statistical inference, and large data analysis to engage big questions about our social world. We have a structured curriculum that is demanding but accessible for anyone with late-blooming interests in quantitative or social scientific research. We also have substantial merit aid that we can offer.
The best short description of our program is available here.
For international students, Computational Social Science is an approved STEM program for your work authorization in the U.S. That means you will receive three years of work permission, following your graduation from our two-year program.
The paid internship between your first and second year, meanwhile, can be held under your regular student visa, because of the “collaborative” status our program has negotiated with those employers.
Rick Evans, a distinguished computational economist, joined our program as a Senior Lecturer. He built the country’s best undergraduate preparation for computational economics at Brigham Young. His laboratory attracted $1.3 million in outside funding, including a $600,000 NSF grant for his curricular innovations in applied and computational math. Dr. Evans also has a highly promising research agenda, developing a macroeconomic model for the testing of tax policy, that has drawn attention across the political spectrum.
Benjamin Soltoff, a recent Political Science PhD from Penn State, joined us as a Lecturer. He wrote a terrific dissertation examining agenda-setting in state courts, for which he was awarded an NSF doctoral grant. He applied sophisticated computational techniques to see how institutional concerns shape judicial decisions across a range of issues important to state legislatures. He was a fellow in Penn State’s Quantitative Social Science Initiative, and taught at Miami University as a visiting professor. He is proficient in Python, R, machine learning, STATA, and the manipulation of GIT repositories.
Ging Cee Ng, a fifth-year in the Department of Economics, joined our program as a preceptor. She had a Sociology and Statistics background before starting the doctoral program. She advises our students on their course selections, serves as a TA for two of our core classes, sees to the administrative needs of our Computation Workshop, and runs an MA Proposal Workshop in the Spring. She also has four years of work experience with the Federal Reserve Bank of New York.
We expect most of our Computation students to go on for PhD study in their chosen social science discipline. The training we provide will make them maximally competitive at leading departments in their field. We will draw on our experience placing students for the PhD in a neighboring MA program, the MA Program in the Social Sciences (MAPSS), where we have had a 91% funded PhD placement rate for over a decade.
Students who decide not to pursue the PhD will find weekly support with a structured curriculum of professional development workshops. We have an in-house Director of Career Services who will facilitate internships between the first and second year, and work with students on an individual basis as they seek employment afterwards.
The mathematical components of the degree can be formidable, but are designed to ramp up in a way that is accessible for all students. You’ll find a good description of the curriculum on the program’s webpage, under MA Program Requirements.
As a rule of thumb, we expect all admitted students to have a quantitative GRE score of 157 or better, placing them in the top 30% of all test takers.
There are no formal math or computer science prerequisites for the program. There will be an intensive summer math camp to assist students who may have had less exposure to linear algebra, differential/integral calculus, and statistics.
That summer math camp will also be a useful refresher for anyone who has not done that kind of work recently.
The MA thesis will be written under the direct supervision of a Computation faculty member, as a part of a three-course “research commitment” in the second year of study.
We have 26 students in this year’s cohort. 76% are international. Nearly 45% are coming from outside the social sciences, with Engineering, Computer Science, Business, and Physical Science backgrounds. 59% are women. The average quantitative GRE score is 89%. We expect 25 students to join us next year.
We provide significant financial aid, with most students earning an award of one-half tuition in the first year, and two-thirds tuition in the second, if they achieve a modest 3.4 GPA. (A threshold reached by 92% of our MA students in other Divisional programs.)
Our very best candidates come in at two-thirds or full tuition in year one.
Courses are selected from the regular graduate offerings at the University. You can get a good sense of the available options by going to this link.
Many of our Computation students will seek and find RAships with UChicago faculty. Given the intense academic demands of the program, we recommend that students start with a 5 hour per week commitment and see if they can handle 10.
At the University of Chicago, graduate students cannot teach other students until their 3rd year of graduate study. Computation students can serve as RAs but not as TAs.
There are a variety of other on-campus employment opportunities, including work at the Regenstein library, the Smart Museum, and the Oriental Institute, or in part-time administrative positions at one of the 140 Centers and Institutes we have on campus.
As part of their degree requirements, all students attend our weekly Computational Social Science Workshop.
The Workshop gives you a chance to see emergent computational work in the social sciences, to learn new methodological tools, to meet leading computational researchers from around the world, and to forge connections with faculty and students across campus.