# Undergraduate and graduate training in neural computation and engineering

> **NIH NIH T90** · UNIVERSITY OF WASHINGTON · 2020 · $112,238

## Abstract

Summary
This proposal continues and evolves an undergraduate and graduate (NRSA and non-NRSA) Training
Program in Neural Computation and Engineering. The University of Washington has a rich history
and a large and growing breadth of active teaching and research in this area, with faculty mentors
distributed through many departments and schools, including Physiology and Biophysics, Biological
Structure, Computer Science and Engineering, Applied Math, Biology, Psychology and Bioengineering.
This program evolves the extremely successful previous five-year program which saw the development
of an active and highly visible training program, including new undergraduate and graduate program,
website, community activities, to take advantage of new opportunities and momentum in Seattle.
Support for undergraduate and graduate education and research will enhance interaction between
theorists and experimentalists; expand and integrate coursework in emerging approaches in
neuroscience, particularly novel offerings in neuroengineering and big data; enhance interactions
between undergraduate and graduate students; provide opportunities for undergraduate research and
draw together the community across campus to strengthen our already excellent interdisciplinary
exchange and collaboration. The undergraduate training program is a 2-year sequence in
computational neuroscience, with support for 6 trainees yearly from neurobiology or from a
computational/engineering major (Physics, Computer Science and Engineering, Bioengineering,
Applied and Computational Mathematics). Trainees take a core curriculum including a research
seminar, a choice of laboratory neurobiology sequence and common quantitative courses. Choice of
additional electives in an individualized curriculum and career development is guided by a mentoring
committee. All students will complete at least 1 and preferably 4 quarters of mentored laboratory
research. The graduate training program will support up to 6 students from multiple graduate
programs. Students will apply for training grant support at the end of the first year and carry out a core
curriculum consisting of neurobiology, quantitative and journal club courses. Individually tailored
curricula including electives selected from offerings in computational neuroscience, mathematics,
computer science and physics will be devised in consultation with a mentoring committee. Trainees will
have access to the UW/Allen Institute Summer Workshop for the Dynamic Brain on San Juan Island. All
trainees will attend a regular seminar and and present their research at an annual retreat. The program
will be co-directed by Profs. Adrienne Fairhall, Physiology and Biophysics and Eric Shea-Brown,
Applied Mathematics, assisted by Leadership Team Prof. Bill Moody, Director, Undergraduate
Neurobiology Program and Prof. David Perkel, Director, Neuroscience Graduate Program.

## Key facts

- **NIH application ID:** 10002199
- **Project number:** 5T90DA032436-10
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Adrienne L Fairhall
- **Activity code:** T90 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $112,238
- **Award type:** 5
- **Project period:** 2011-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10002199

## Citation

> US National Institutes of Health, RePORTER application 10002199, Undergraduate and graduate training in neural computation and engineering (5T90DA032436-10). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10002199. Licensed CC0.

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