# Integrated Regional Training Program in Environmental Health Sciences

> **NIH NIH T32** · OREGON STATE UNIVERSITY · 2021 · $85,722

## Abstract

Project summary
This supplementary project will develop nine, 1-hour training modules designed to equip Oregon State
University trainees supported by parent Grant 5T32ES007060: “Integrated Regional Training Program in
Environmental Health Sciences” with the competencies and skills needed to make Environmental Health
Sciences (EHS) data FAIR (Findable, Accessible, Interoperable, and Reusable) and AI/ML (Artificial
Intelligence and Machine Language) -ready. This project will address a gap in our current training activities
available for current pre- and post- doctoral trainees in our T32 Training Program, our Superfund Center
Research Experience and Training Coordination Core, and Environmental Health Sciences Center Professional
Development Core, our umbrella Toxicology Graduate Program curriculum here at OSU, our regional partner
training institutions for our T32, SRP and EHSC grants (Pacific Northwest National Labs; University of
Washington, University of New Mexico (a major HSI), UC-Davis and UC-Berkeley) as well as our training
consortium of regional universities (Univ of Oregon, Portland State University, Oregon Health Sciences
University (OHSU) and 14 regional 4-year colleges and community colleges (including four minority-serving
institutions). We will hire one additional data scientist to collaborate with the scientists in the Data Analytics
group in our OSU Center for Quantitative Life Sciences (CQLS) and Dr. Katrina Waters at Pacific Northwest
National Labs (Director of the OSU SRP Data Management and Analysis Core -DMAC) to develop the web-
based asynchronous training modules which will include real-time self-assessment exercises and evaluation by
participants. The 9 training modules will provide three levels of expertise to participants completing the
modules: Basic, Intermediate, and Advanced. The training materials will cover the basic concepts
of information science and `big data' artificial intelligence, and machine learning (AI/ML), and the critical
importance of designing their research projects to generate EHS data compatible with FAIR requirements.
Trainees completing all three modules will be able to actively participate in the data analytics process of
developing, accessing and sharing FAIR-compliant data sets for reuse. The learning modules will each confer
skill sets addressing the following three categories of competency at increasing levels of sophistication and
complexity: 1) Data integration; 2) Multimodal data analytics; and 3) Machine Learning and Artificial
Intelligence. These training materials will be made freely available nationally and internationally on our
university web pages.

## Key facts

- **NIH application ID:** 10406091
- **Project number:** 3T32ES007060-42S1
- **Recipient organization:** OREGON STATE UNIVERSITY
- **Principal Investigator:** Siva Kumar Kolluri
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $85,722
- **Award type:** 3
- **Project period:** 1979-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406091

## Citation

> US National Institutes of Health, RePORTER application 10406091, Integrated Regional Training Program in Environmental Health Sciences (3T32ES007060-42S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10406091. Licensed CC0.

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