Education | Computational Neuroscience Initiative

Graduate Education

Interdisciplinary Training in Computational Neuroscience (ITCN)

Applications are open for the Interdisciplinary Training program in Computational Neuroscience. PhD students from neuroscience, bioengineering, psychology or physics graduate groups are welcome to apply.

The Computational Neuroscience Initiative at the University of Pennsylvania offers a new program for Interdisciplinary Training in Computational Neuroscience (ITCN) at the doctoral level. The goal of the ITCN is to train a new generation of scientists who will make quantitative links between properties of the brain and properties of the mind. ITCN trainees will learn to use computational methodology to interpret experimental results, build predictive models of brain function that inform the design of the experiments, and support an ever-growing list of applications from brain-machine interfaces in the clinic to cutting-edge forms of artificial intelligence.

The ITCN brings together students and faculty from Penn’s PhD programs in Neuroscience (Biomedical Graduate Studies, Perelman School of Medicine), Bioengineering (School of Engineering and Applied Science), Physics (School of Arts and Sciences), and Psychology (School of Arts and Sciences). To join the ITCN, students first apply to one of those "home" PhD programs. Once admitted, students then typically apply to the ITCN before starting classes in their first year. Those selected meet with the ITCN Advisory Committee, both individually and as a group, to develop individualized training plans that meet the goals and requirements of the ITCN and each student’s home program. These plans include coursework, research, and other activities that aim to build both expertise in computational neuroscience and a sense of community in the ITC Details are provided below.

The ITCN embraces diversity and inclusion in their many forms, including welcoming students with a broad range of personal, professional, and academic backgrounds into both our training program and the field of computational neuroscience as a whole.

Application. Prospective PhD students from Neuroscience, Bioengineering, Physics, or Psychology can apply by emailing Jessica Marcus at jmarcus@sas.upenn.edu. Students typically apply to the ITCN before starting classes in their first PhD year, although we will also consider applications from students in more advanced years who believe they will be able to meet our academic requirements. Selection into the ITCN does not require a background in computational neuroscience. Instead, we require: 1) a brief (~½ page) essay describing why you want to join the ITCN and how it would fit into your training and career plans; 2) written permission from your Graduate Chair (and, for MD-PhD or VMD-PhD students, the Director of your Combined Degree Program); and 3) if you are not in one of our four participating programs, descriptions of the funding source(s) and course and research requirements for your home PhD program. Please contact us directly with any questions: Vijay Balasubramanian, Maria Geffen, and/or Joshua Gold.

Funding. ITCN trainees are currently expected to be funded via their home PhD programs. This funding may (but is not required to) include support from one of several training grants at Penn with close associations with our training program, including (please contact the PI(s) for more details about each training grant): 1) for NGG students, the Neuroscience Training Grant (PIs: Joshua Gold and Minghong Ma); 2) for students training in vision science, the Vision Training Grant (PI: Jessica Morgan); and 3) for students training in auditory neuroscience, the CANAC training program: Computational Approaches to the Neuroscience of Audition and Communication (PIs: Yale Cohen, Vijay Balasubramanian, and Maria Geffen).

Advising. The ITCN Advisory Committee consists of Vijay Balasubramanian, Maria Geffen, and Joshua Gold. Each ITCN trainee meets with the full Advisory Committee on yearly basis to establish academic and career plans and monitor progress. A major goal of ITCN advising is to ensure that each trainee is able to balance the training components of the ITCN with the training components of their home program.

Courses. ITCN trainees are expected to take all of the required courses from their home program, and then use their electives to fulfill ITCN course requirements. These requirements are:

PHYS 585: Theoretical and Computational Neuroscience
Two or three electives chosen (with the help of the Advisory Committee) to provide appropriate foundations for each trainee, selected from the many courses offered at Penn. Possible course include:
BE 5210/521: Brain-Computer Interfaces
BE 5660/566: Network Neuroscience
CIS 5200/520: Machine Learning
ESE 3130/313: Robotics and Bio-inspired Systems
ESE 4060/406: Control of Systems
ESE 4080/408: Communication Systems
ESE 5390/539: Hardware/Software Co-Design for Machine Learning
ESE 5730/573: Building Brains in Silicon
ESE 6740/674: Information Theory
MATH 2400/MATH 240: Differential Equations and Linear Algebra
MATH 2410/MATH 241: Fourier Analysis and Complex Analysis
NGG 573: Systems Neuroscience
PHYS 662 Statistical Physics
PHYS 2280/PHYS 280: Physical models of Biological Systems
PSYC 5110: Probabilistic Models of Perception
PSYC 3790/BIBB 473: Neuroeconomics
PSYC 719 Experimental Methods in Perception
PSYC 739 Probabilistic Models in Perception and Cognition

Research. ITCN trainees are expected to fulfill all laboratory rotation requirements from their home program, which may include a combination of labs that are and are not affiliated with the ITCN. We expect trainees to ultimately join a dissertation laboratory affiliated with the ITCN (i.e., CNI laboratories) but will provide exceptions or add the laboratory to the ITCN as needed.

Other Activities. ITCN trainees are expected to participate in the weekly trainee-led CNI+/- Journal Club and attend biweekly CNI seminars (listed here). There are additional CNI-sponsored workshops and activities determined on an annual basis, such as supervised participation in Neuromatch academy or direct workshops.