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M.S. Students

The Master of Science (M.S.) program in Cognitive and Information Sciences (CIS) trains students in experimental, analytical, and computational methods and theories of human cognition, perception, behavior, and interaction. Students may concentrate on applied methods and skills useful to careers in data science, careers at the interface of humans and technology, and other nonacademic career paths that stem from cognitive science training. The program also allows students to concentrate their studies on basic research in preparation for continued study at the doctoral level, at UC Merced or elsewhere.

Cognitive science is a growing interdisciplinary field that combines knowledge and techniques from the social, natural, and computational sciences and philosophy to address problems related to mind, brain, and behavior. Due to the intrinsic interdisciplinarity of cognitive science, researchers often need training in multiple disciplines for advanced study, beyond what is typically covered in most undergraduate degree programs. The M.S. program addresses this growing need. Students may choose either a thesis track or a capstone track; both tracks are designed so that coursework may be completed over a single year in two full-load semesters — the capstone or thesis may then be completed by the end of summer. Specific program requirements for the M.S. degree in Cognitive & Information Sciences are listed below.

Course Requirements

The following courses are required for the completion of the Ph.D. degree:

  • COGS 201 & 202: Foundations in Cognitive Science. These two courses cover the main theoretical frameworks (201) and methodologies (202) of contemporary cognitive science, with the historical context needed to appreciate progress and directions in the field.
  • COGS 210: Statistics for Cognitive Science
  • ONE graduate-level course in CIS-related computational science.Options include:
    • COGS 203: Neural Networks in Cognitive Science
    • COGS 204: Complex Adaptive Systems
    • COGS 212: Methods of Data Science
    • COGS 222: Modeling Social Behavior
    • COGS 223: Computational Cognitive Neuroscience
  • TWO other graduate-level courses in COGS or other related programs. Special topics are regularly offered as COGS 269 or COGS 285.

Typical Timeline and Sequence of Events

The below table is only provided as an example: timeline may vary between individuals. However, COGS201/202: Foundations 1 & 2 should be taken in the fall and spring semester respectively

Year One



COGS 201: Foundations I

COGS 202: Foundations II

COGS 204: Complex Adaptive Systems

COGS 210: Statistics for Cognitive Science

COGS 230: Cognitive Neuroscience

COGS 278: Cognitive Science of Emotions





Complete Thesis or Capstone Project

Master’s I Thesis Option

The Thesis option will consist of an original research project. The project may be empirical or computational, and it will include data collection and/or analysis to produce and interpret results. The research plan will be developed by the student in consultation with the advisory committee. For an empirical project, the plan will include the research question and hypotheses, the targeted amount of data to be collected, the means and timeframe by which data will be collected, and the types of analyses to be conducted. Plans for computational projects will be analogous but based on simulations or corpus analyses instead of experiments. The thesis will report on the research project and be formatted as a short journal article submission. At the outset, the advisory committee will identify a target journal and submission type. The advisory committee will evaluate the thesis as if it was submitted for publication, and a passing thesis will be equivalent to a review of “revise and resubmit” or better. The thesis does not need to be submitted for publication to earn the M.S. degree.

Should the Thesis Committee determine that the thesis is unacceptable, a recommendation to disqualify the student may be made to the Vice Provost and Dean of Graduate Education. Detailed information and instructions on the submission and filing of the thesis is available in the UCM Thesis and Dissertational Guidelines, available on the Graduate Division website. A schedule of dates for filing the thesis in final form are published on the Graduate Division website in the Dates and Deadlines section.

Master’s II Capstone Option

Students opting for the capstone track will meet with their advisory committee by the beginning of their second semester to formulate a capstone activity. Each student and committee may choose from one of the three options listed below, or they may formulate an individualized capstone comparable in workload and rigor pending approval of the advising committee. For all capstone projects, the advisory committee will evaluate the document against the deliverables specified in their agreement.

  • Literature Review. The advisory committee will work with the student to formulate one or more research questions, an outline, and reference list. The resulting paper will be about 10-20 double-spaced pages in length, not including references and other supporting material, and is expected to summarize the existing literature related to the specified research question(s).
  • Computational Project. The advisory committee will work with the student to formulate a coding project, including the targeted platform, functionality, and tests. The project will culminate in the code and a 10-20 page (double-spaced) technical report.
  • Industry Internship. CIS faculty members have connections with industry partners (primarily, though not exclusively, in Silicon Valley), and students may make connections on their own to find summer internships, paid or unpaid. If a student is able to find a relevant industry internship, they may fulfill their capstone requirement by writing a brief report summarizing the experience and relating it to the relevant scholarship in cognitive science. Although the CIS department may be able to direct some students to internship opportunities, there is no guarantee that the faculty will be able to facilitate internships.

Change of Degree level: M.S. to Ph.D.

M.S. students wishing to enter the CIS Ph.D. program can apply internally to transfer to the Ph.D. program at times approved by the Admissions Committee. All the requirements for admission to the Ph.D. program will apply, and admission to the M.S. program does not guarantee admission to the Ph.D. program.

A Note from Jaskanwaljeet Kaur & Shannon Proksch:
Embarking on and finishing an entire masters degree in only one calendar year is no small feat! By the time you’ve reached this stage, you’ve finished the full curriculum of CIS graduate program coursework. Embarking on a master’s thesis or a capstone may sound daunting, but know that you have learned you need to successfully complete these projects. Furthermore, as you are applying for industry internships, industry/government/etc careers, or even for Ph.D. programs, you now have a suite of advanced computational and statistical skills in your toolkit. Many of our CIS alumni working in industry+ careers have come back to speak with current graduates, noting that this coursework more than prepared them for the computational or data analytics skills necessary in their careers at facebook, pymetrics, Accenture, and more. In fact, the most important training that CIS alumni take from their time here is the ability to solve problems, to learn quickly, and to communicate their work with stakeholders outside their area of expertise. While you’re here completing your coursework and your Thesis/Capstone projects, be sure to practice those communication skills by discussing your research with members of your masters cohort and even Ph.D. students within the CIS program, keeping an eye on your post-masters program goals. And with that, have fun, do great research, and we’re excited to see where you go from here!