# Undergraduate and Graduate Training in Computational Neuroscience and Data Analysis

> **NIH NIH R90** · BRANDEIS UNIVERSITY · 2024 · $247,968

## Abstract

Project Summary
The goal of this training program entitled “Training in Computational Neuroscience and Data Analysis” is 
to help undergraduate and predoctoral students gain the knowledge, skills, and attitudes they need to 
flourish in a scientific career that brings quantitative approaches to the study of neuroscience and 
behavior. This new program arises from a prior training program in Computational Neuroscience at 
Brandeis University that expired recently after 10 years of NIDA support. Given the increasing 
importance of machine learning in data analysis and solving of data-rich scientific problems, coupled with 
recent Brandeis hires in the field, our new program will include more participation from computer science 
faculty with expertise in the field. Also, given the recent introduction of an applied mathematics major at 
Brandeis and associated new faculty in the field, we have doubled the number of training labs with 
students working on mathematical modeling in neuroscience. The proposed program requests funding 
to support 6 undergraduates, 4 NRSA eligible graduate students, and 2 non-NRSA eligible graduate 
students each year. We will target two cohorts of prospective trainees: 1) Individuals with strong prior 
experience with quantitative methods who wish to work in neuroscience. 2) Individuals with backgrounds 
in psychology, neuroscience and biology who wish to learn to employ quantitative and computational 
methods to tackle important problems in neuroscience. We will continue prioritizing outreach activities 
aimed at ensuring trainees from underrepresented populations are included in our program. Students will 
have two complementary mentors so they participate in labs with both quantitative and experimental 
approaches to neuroscience. The 26 training faculty have research expertise ranging from human 
cognition to cellular and molecular neuroscience, so a wide variety of research problems, at numerous 
levels of analysis are available to trainees. The training faculty were chosen based on demonstrated 
commitment to the use of theoretical and computational methods and interdisciplinary collaboration to 
understand the nervous system in health and disease. Students will take courses in statistics, data 
analysis, computational neuroscience, obtain skills in building models of neurons, synapses, and 
networks, and employ these in a variety of independent research projects. In addition to course work and 
laboratory research, students and trainees will be engaged in a large number of other activities designed 
to enhance their speaking skills, writing skills, and ability to collaborate with other scientists. All students 
and trainees will receive training in the responsible conduct of science and will interact with senior 
scientists at other institutions.

## Key facts

- **NIH application ID:** 10929534
- **Project number:** 5R90DA060341-02
- **Recipient organization:** BRANDEIS UNIVERSITY
- **Principal Investigator:** PAUL MILLER
- **Activity code:** R90 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $247,968
- **Award type:** 5
- **Project period:** 2023-09-15 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10929534

## Citation

> US National Institutes of Health, RePORTER application 10929534, Undergraduate and Graduate Training in Computational Neuroscience and Data Analysis (5R90DA060341-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10929534. Licensed CC0.

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