# Training Program in Neural Computation and Engineering

> **NIH NIH R90** · UNIVERSITY OF WASHINGTON · 2020 · $1

## 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:** 10002200
- **Project number:** 5R90DA033461-10
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Adrienne L Fairhall
- **Activity code:** R90 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1
- **Award type:** 5
- **Project period:** 2011-09-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10002200

## Citation

> US National Institutes of Health, RePORTER application 10002200, Training Program in Neural Computation and Engineering (5R90DA033461-10). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10002200. Licensed CC0.

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