# NYU-Moi Data Science for Social Determinants Training Program

> **NIH NIH U2R** · NEW YORK UNIVERSITY · 2021 · $349,655

## Abstract

Project Summary
The overarching goal of the Data Science for Social Determinants (DSSD) at New York University, Moi University
and Brown University is to develop future leaders in data science who are equipped to develop and analyze data
to better leverage deep and rich survey as well as internet and other digitized data sources that can help us
capture information on the social determinants of health. DSSD's design will rapidly expand the local base of
expertise via curriculum development, resulting in 2 PhD (4-year training) and 6 total postdoctoral (2-year) and
faculty trainees (12-14 month) will train at NYU, while 8 Masters and 2 PhD trainees will commence or complete
training (2-year and 4-year training, respectively) through newly developed data science tracks at Moi University.
Connecting with local data science industries and organizations (IBM, Deep Learning Indaba, DataKind,
AI.Kenya and Aga Khan University Nairobi and Karachi) will bring in and create intellectual meeting spaces for
a wide pool and variety of talented trainees from both data science and health backgrounds, to propel and
sustainably advance data science capacity in Kenyan institutions as well as the DSI-consortium.

## Key facts

- **NIH application ID:** 10320171
- **Project number:** 1U2RTW012121-01
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** RUMI CHUNARA
- **Activity code:** U2R (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $349,655
- **Award type:** 1
- **Project period:** 2021-09-22 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10320171

## Citation

> US National Institutes of Health, RePORTER application 10320171, NYU-Moi Data Science for Social Determinants Training Program (1U2RTW012121-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10320171. Licensed CC0.

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