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 yearlong participation in research and requires completion of certain coursework (detailed below) before the end of the fellow’s 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.
Fellowship nominations and applications
Applications will be solicited in February every year, and if fellowships are available, again in July. Contact Tai Sing Lee (
) at Carnegie Mellon or Jon Johnson (
) at the University of Pittsburgh for more information. To apply to the program, fellowship applicants need to be nominated by a faculty mentor as follows:
- The student applicant contacts a potential faculty mentor and they discuss a research project
- The student applicant prepares and sends to their prospective faculty mentor
- A one-paragraph description of their intended project
- A description of their plan to complete the fellowship course requirements (below)
- A copy of their transcript
- Their resume
- The faculty member sends to Tai Sing Lee and Jon Johnson an email in which they nominate the student applicant, and attach items a – d.
Course requirements and options
Students taking the full training program will be required to take courses in the following subject areas. 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).
In addition to working in the lab during the summer, fellows are expected to participate in the summer program and attend a series of computational neuroscience lectures with the students in the Neural Computation Summer Program. Fellows are expected to work for 10 weeks in the summer full time, and to be in town during the entire period of the summer program. A small shift in schedule is allowed contingent on approval of the fellow’s mentor. Continuation of a fellowship is contingent on satisfactory research progress each semester. There are three milestones in the fellowship program: (1) A 6-page report is expected from fellows describing research progress at the end of summer. (2) In January, fellows are expected to give a presentation of their research progress to the group of fellows. (3) By May, fellows are expected to submit a 10-page paper, in J. Neuroscience format, that has received their mentor's approval.