Training program to improve skills in AI for addiction research
Official title: A Multimodal and Interdisciplinary Data Science Training Program to Enhance a Diverse Workforce for Addiction Research
Funded at University of Mississippi · NIH-11018399 · Data updated 2026-11-12
This program is designed to help students, especially those from underrepresented backgrounds, learn how to use Artificial Intelligence and Machine Learning to study addiction, with fun activities like webinars and hands-on training at research labs across three Mississippi universities.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Mississippi NIH-funded |
| Lab location | 1 site (University, United States) |
| Project start | September 15, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $128,761 |
| NIH project number | 1R25DA061764-01 |
| Project ID | NIH-11018399 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this program are undergraduate and graduate students, particularly those from underrepresented backgrounds interested in data science and addiction research.
✕Less likely to help
Patients who are not students or who do not have an interest in pursuing a career in data science or addiction research may not benefit from this program.
What this research studies
This program aims to enhance the skills of students in using Artificial Intelligence (AI) and Machine Learning (ML) for addiction research. It involves a collaborative effort across three universities in Mississippi, focusing on creating a diverse workforce in data science. Participants will engage in various learning activities, including webinars, summer academies, and hands-on training in research labs. The program specifically targets underrepresented students to ensure inclusivity in the field of addiction research.
Why it matters
Potential benefit: If successful, this research could lead to a more skilled and diverse workforce capable of advancing addiction research through innovative AI and ML techniques.
How similar studies have gone: While the specific approach of this program may be novel, there have been successful initiatives in other regions that focus on training diverse students in data science for health-related research.
Where this research is happening
-
University of Mississippi
University, United States Active
Researchers
- Principal investigator: Zhang, Saijun — University of Mississippi
- Study coordinator: Zhang, Saijun
Related research
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.