# Biostatistics for Research in Genomics and Cancer

> **NIH NIH T32** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2020 · $208,980

## Abstract

Project Summary
This 5 year program is designed to continue to train predoctoral (PhD) students in statistical
genomics with the major emphasis in cancer genomics. The goal is to train biostatisticians in
the biology, etiology, and genetics of cancer, as well as to train them to conduct state-of-the-art
biostatistical methodologic research relevant to the genomics of cancer as well as in related
areas of genomics. The goal is to also produce biostatisticians who can collaborate with other
scientific researchers and oncologists on research issues related to genomics and cancer. The
typical predoctoral trainee will be a college graduate or master's level graduate with an excellent
academic record appropriate for this training area. Funding is requested for the support of 5
predoctoral trainees. The Department of Biostatistics at UNC is one of the largest in the world,
and has highly qualified personnel and the available facilities to provide the most
comprehensive predoctoral and postdoctoral training in this research area. Several members
from the Department of Genetics and the Bioinformatics and Computational Biology (BCB)
program will be deeply involved in all phases of this training program and will play an integral
role in this training program.

## Key facts

- **NIH application ID:** 9975091
- **Project number:** 5T32CA106209-15
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** JOSEPH G IBRAHIM
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $208,980
- **Award type:** 5
- **Project period:** 2004-05-01 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9975091

## Citation

> US National Institutes of Health, RePORTER application 9975091, Biostatistics for Research in Genomics and Cancer (5T32CA106209-15). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9975091. Licensed CC0.

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