Undergraduate Research Fellowships in Computational Neuroscience
The goal of this program is to attract a select group of students to engage in undergraduate research in the area of computational neuroscience. This program involves year long participation in research and requires completion of certain coursework (detailed below) before the end of your senior year. In return, the program provides a stipend of approximately $11,000 for the year, plus the possibility of travel funds to attend meetings and workshops.
Applications will be solicited in February and September every year. Contact Tai Sing Lee (
) at Carnegie Mellon or Doug Weber (
) at the University of Pittsburgh for more information.
Course requirements and options
Students taking the full training program will be required to take courses in the following subject areas, plus a capstone course in their senior year. All listed courses are currently taught annually or biannually.
a. Introductory Neuroscience
All students will take a course that covers basic principles of cellular and systems neuroscience.
Examples: CMU - Biology of the Brain (Bio 03-361). Pitt - Introduction to Neuroscience (Neurosci 1000).
b. Neurophysiology or Psychology
Students with a more biological focus should take a neurophysiology course whereas students whose interests are more in the realm of cognitive modeling should take a psychology course.
Examples: CMU - Introduction to Psychology (Psych 85-102). Pitt - Neurophysiology (Neurosci 1012).
c. Linear algebra
Students will take a course in linear algebra and matrix theory. Members of the training faculty feel this is an essential prerequisite for many different courses in mathematics, computer science and engineering.
Examples: CMU Matrix Algebra (Math 21-241). Pitt - Numerical Linear Algebra (Math 1080).
Students will take a course in statistical methods.
Examples: CMU - Statistics for Lab Science (Stats 36-247). Pitt - Applied Statistical Methods (Stats-1000)
e. Computer science
Students will take a course covering the fundamentals of computer programming.
Examples: CMU - Intermediate/Advanced Programming (CS 15-111). Pitt - Intro to Computer Programming (CS 0007)
f. Computational Neuroscience
Students will take at least one course in the field of computational neuroscience.
Examples: CMU - Neural Computation (15-386), Computational Models of Neural Systems (15-880). Pitt - Intro to Mathematical Neuroscience (MATH 1800), Computational Neuroscience Methods (Math 3375), Mathematical Neuroscience (Math 3370).
All students in the program will be encouraged to become involved in undergraduate research as early in their career as possible. To be considered for funding through the program, students will need to have identified a preceptor or co-preceptors and be involved in a research project. Students will be encouraged to develop a research and education plan with their advisor in advance of starting to work in the lab. In this way, students can be advised not only about the research plan, but also about what courses would best prepare them to undertake the project.