# FAIR Data Competency and Machine Learning Readiness for Biomedical Scientists

> **NIH NIH K12** · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · 2021 · $85,600

## Abstract

Project Summary/Abstract
The Academic Science Education and Research Training (ASERT) program for postdoctoral scholars at the
University of New Mexico (UNM) matches PhD graduates with outstanding biomedical research mentors and
engages New Mexico’s diverse populations through effective science education collaborations with minority
serving institution (MSI) and national tribal college partners. The overall objective of ASERT is to contribute to
the number of junior faculty across the country with the training and experience to succeed in all facets of
academic life at institutions that are likely to have highly diverse student populations and where
interdisciplinary, collaborative research is essential for success. The present supplement request will expand
the professional development of ASERT fellows and interested associate members in Findable, Accessible,
Interoperable and Reusable (FAIR) data management and data analyses using machine learning. The
proposed training is a critical training need for investigators in the biomedical sciences due to the increasing
complexity of the datasets, a need for improved data stewardship to ensure data usability, and to enable new
discoveries through effective use of existing data and facility in linking to new data. Faculty with extensive
expertise in FAIR data management, machine learning, and biostatistics will develop and implement a training
program consisting of eight modules that encompass the overarching principles of: 1) Obtaining data / Data
management and processing; 2) model training; 3) model evaluation; 4) model improvement. There is strong
institutional support for the training program beyond the supplement period, including opportunities for a
deeper dive into modern AI/ML techniques, and managing diverse data sets in accordance with FAIR
standards afforded by an advanced, mentored Biomedical Data Science course. Fellows will share information
on opportunities in data science with undergraduate students at ASERT IRACDA partnered Minority Serving
Institutions. Publication and presentation at the National IRACDA Conference will serve to further disseminate
and share training resources.

## Key facts

- **NIH application ID:** 10406055
- **Project number:** 3K12GM088021-13S1
- **Recipient organization:** UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR
- **Principal Investigator:** Angela Wandinger-Ness
- **Activity code:** K12 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $85,600
- **Award type:** 3
- **Project period:** 2009-09-15 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406055

## Citation

> US National Institutes of Health, RePORTER application 10406055, FAIR Data Competency and Machine Learning Readiness for Biomedical Scientists (3K12GM088021-13S1). Retrieved via AI Analytics 2026-06-15 from https://api.ai-analytics.org/grant/nih/10406055. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*