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 end of summer. An outline of the program’s requirements is below.
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Application deadline is December 1.
Funding
Terminal M.S. students are not expected to be funded by either teaching assistantships or research grants. That said, graduate students are encouraged to seek out grant funding and employment opportunities on campus to support their research.
Coursework
The following courses are required for the completion of the M.S. 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.
Thesis or Capstone Project
Students may choose either Master’s I (thesis option) or II (capstone option). The thesis will be an original research contribution to cognitive science, broadly construed. The capstone may be a literature review, programming project, industry internship (including a written report), or equivalent activity formulated and approved with the student’s advisory committee. The thesis or capstone are expected to be completed the summer following completion of coursework.
Thesis. The thesis option, intended for those students pursuing an academic track, involves the completion of an original research project. This may be empirical or computational and will include data collection and/or analysis to produce and interpret novel results. An advisory committee will meet with the student at the beginning of the second semester to formulate a research plan. For empirical projects, the plan will include the research question and hypotheses, the targeted data to be collected, and the types of analyses to be conducted. Plans for computational projects will be analogous, but based on simulations or corpus analyses rather than experiments. The thesis will be formatted as a short journal article submission.
Capstone Project. The capstone option is intended for those students pursuing a career in industry. Students and their advisory committee will choose from one of the three options listed below, or formulate an individualized capstone comparable in workload and rigor:
Literature Review. A paper summarizing the existing literature related to a research topic identified by the student and their advisory committee.
Computational Project. A coding project, including a targeted platform, functionality, and tests, culminating in the code and a technical report.
Industry Internship. CIS faculty members have connections with industry partners which may potentially be leveraged to arrange summer internships, or students may make connections on their own. Students who perform summer internships may write a report summarizing the experience and relating it to the relevant scholarship in cognitive science.
Program Learning Outcomes
1. Foundational Knowledge in Cognitive and Information Science
Students will gain the ability to digest and analyze technical articles in cognitive science, including the methods, results, and implications for theory and applications.
2. Foundational Skills in Cognitive and Information Science
Students will gain the ability to do one or more of the following: 1) program basic cognitive science experiments and analyze the results; 2) analyze large-scale datasets such as language, image, or video corpora; 3) program and run computer simulations of cognitive or behavioral processes; or 4) apply machine learning algorithms to datasets containing measures of behavioral or neural activity.
3. Research Project Design
Students will be gain the ability to plan small research projects involving behavioral and/or cognitive phenomena, including the following components: research questions, competing hypotheses, and empirical or computational methods of inquiry.
4. Scientific and Professional Writing
Students will gain the ability to write short scientific articles or similarly brief technical or professional reports.
Alumni
Earning your master's or Ph.D. from UC Merced means something. Follow in the footsteps of our alumni, many of whom now hold faculty appointments and meaningful positions in the public and private sectors.