The Cognitive and Information Sciences (CIS) Ph.D. program emphasizes collaborative and interdisciplinary research training. 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. Typically, CIS graduate students work closely with one or more faculty in pursuing scientific research, while taking a series of courses that can be tailored to the specific needs and specialization of the student. An outline of the program’s requirements is below.
Application deadline is December 1. To see which faculty are recruiting, and their research interests, please see the faculty with asterisks (*) beside their name here. Prospective PhD students may contact potential advisors by email to see if their research interests are a good fit with the research currently being conducted in the lab; it can help to include a CV when reaching out.
The CIS program has multiple means of supporting PhD students. Primarily, during the academic year, students serve as teaching assistants to faculty members. This position provides a full stipend and complete tuition waiver. In addition, some students spend a few semesters on a faculty member’s grant project, providing support through research specifically. Students almost always receive some form of summer stipend in order to support their research activities during the off-season. For more details aboutUC Merced’s internal awards and fellowships: https://graduatedivision.ucmerced.edu/funding/internal.
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.
- COGS 250: Minds, Technology, and Society. Ph.D. students must enroll in this course every semester they are enrolled in the program and in residence at UC Merced.
Research Projects in First and Second Years
Each student must give a talk on a research project that they are working on at the end of their first year, and another at the end of their second year. First- and second-year students must also write a research report each year. Each report is to be formatted in a manner consistent with submission for academic publication.
Students must complete at least six semesters of full-time academic residence at UC Merced. In addition, before advancing to candidacy, Ph.D. students must be registered in University courses as a full-time student for at least four semesters.
CIS requires all graduate students pursuing the Ph.D. to acquire teaching experience at the post-secondary level under faculty supervision, for at least two semesters at UC Merced. This requirement is typically satisfied by appointment as a Teaching Assistant or Teaching Fellow in undergraduate courses.
Students must deliver a full-length (usually 45-60 minutes) technical seminar (an oral presentation on the student’s original research) at least once while in residence at UCM. This can be fulfilled by offering a presentation at the weekly CIS Brownbag meeting, however the seminar may be given in any scholarly public venue that is approved by the student’s advisory committee (prior to the time the talk is given). At least one CIS faculty member must be present at the seminar.
Integrative Review Papers
Graduates of the Ph.D. program in CIS are expected to possess a broad understanding of the full range of theories and methods employed in this interdisciplinary field. In order to assess the breadth of student knowledge, and in order to encourage an integrated view of the varied contributions that different disciplines make to cognitive and information sciences, each student must compose an integrative review (IR) paper. This paper will review and synthesize literature that is relevant or related to the student’s topic(s) of study, with the view that each research topic studied in CIS can be tackled from multiple perspectives and levels of organization, using different methods and approaches. The paper should integrate, at a deep level, research, theories, and methods from each of six approaches to CIS. Five approaches are set in advance:
- Behavioral science
- Computational modeling
- Language and linguistics
In addition, the IR paper should also integrate research, theories, and methods from a sixth approach to be decided upon by the student and their Faculty Advisory Committee, reflecting the need for diverse approaches in an interdisciplinary program. Possibilities for this elective approach include (but are not limited to) Cognitive Engineering, Anthropology, Evolutionary Biology, or Education. The IR paper is to be formatted in a manner consistent with submission for academic publication.
Ph.D. Candidacy Examination
Students must pass a candidacy exam, typically in the third or fourth year, in order to begin work on their dissertation. The exam consists of a written dissertation proposal (about 30 pages in length) and an oral defense of the dissertation, which takes place privately with the student’s advisory committee. The oral defense may also include general questions about topics in cognitive science covered in the student’s integrative review papers.
Program Learning Outcomes
Foundational Knowledge in Cognitive and Information Science. Students will be able to digest and analyze technical articles in cognitive science, including the methods, results, and implications for theory and applications. This is a focus of COGS 201 & 202, and may also be learned in other courses and as part of the work toward a dissertation.
Foundational Skills in Cognitive and Information Science. Students will be able 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 computationally sophisticated analytic techniques to datasets relevant to human behavior or neural activity.
Research Project Design. Students will be able 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.
Scientific and Professional Writing. Students will be able to write short scientific articles (about 5 journal pages) or similarly brief technical or professional reports.
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