# University of California Berkeley Chemistry-Biology Interface Training Program

> **NIH NIH T32** · UNIVERSITY OF CALIFORNIA BERKELEY · 2020 · $482,056

## Abstract

PROJECT SUMMARY
This is the third renewal application for the Chemistry-Biology Interface predoctoral training grant
at UC Berkeley. The program provides graduate PhD students with a unique depth of training in
the application of chemical principles and techniques to the investigation and modulation of
biological systems. The program’s goal is to encourage further integration of the fields of
chemistry and biology and prepare students for a future of research at this interface. Key
components of the program include three first-year laboratory rotations among 41 faculty in nine
different departments, specialized didactic training, seminars, annual retreat and career day, and
new in this proposal, enhanced professional and career development programs, expanded
training in scientific communication, and a new academic-industrial partnership in translational
chemical biology with Novartis International. To date, the program has trained over 180 students
with 99 already completing their PhD degrees, 57 during the last grant cycle. Students emerging
from Berkeley with this unique training are positioned to make a significant impact on human
health and biomedical science in both industrial and academic settings.

## Key facts

- **NIH application ID:** 9964828
- **Project number:** 5T32GM066698-17
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Christopher J. Chang
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $482,056
- **Award type:** 5
- **Project period:** 2004-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9964828

## Citation

> US National Institutes of Health, RePORTER application 9964828, University of California Berkeley Chemistry-Biology Interface Training Program (5T32GM066698-17). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9964828. Licensed CC0.

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