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Associate Director of AI/ML Research & Training
Job no: 514271
Work type: Staff
Location: Fort Worth
Categories: Computer Science Counseling, Data Science
Title: Associate Director of AI/ML Research & Training
Employee Classification: Assoc Dir, Program Management
Campus: University of North Texas - Health Science Center
Division: HSC-Div of Rsrch & Innovation
SubDivision-Department: HSC-Health Institutes & Centers
Department: HSC-Inst for Health Disparities-300220
Job Location: Fort Worth
Salary: 92,940.00 - 111,528.00 Depending on Experience
FTE: 1.000000
Retirement Eligibility: TRS Eligible
About Us - Values Overview
Welcome to the University of North Texas System. The UNT System includes the University of North Texas in Denton and Frisco, the University of North Texas at Dallas and UNT Dallas College of Law, and University of North Texas Health Fort Worth. We are the only university system based exclusively in the robust Dallas-Fort Worth region. We are growing with the North Texas region, employing more than 14,000 employees, educating a record 49,000+ students across our system, and awarding nearly 12,000 degrees each year.
We are one team comprised of individuals who are committed to excellence, curiosity and innovation. We are transforming lives and creating economic opportunity through education. We champion a people-first values-based culture where We Care about each other and those we serve. We believe that we are Better Together because we foster an environment of respect, belonging, and access for all. We demonstrate Courageous Integrity through setting exceptional standards and acting in the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your work as part of our UNT System team.
Learn more about the UNT System and how we live our values at www.UNTSystem.edu.
Department Summary
The Institute for Health Disparities (IHD) conducts research, training and community
outreach in the areas of minority health, health disparities and workforce variety.
Constituting the IHD are the Texas Center for Health Disparities, National Research
Mentoring Network, Texas CEAL Consortium, Training Programs, AIM-AHEAD and the NIMHD Endowment.
Position Overview
The Associate Director, AI/ML Research and Training, provides leadership in advancing artificial intelligence and machine learning research and training initiatives within IHD. The role supports interdisciplinary research, develops training programs, and contributes to extramural funding efforts to enhance institutional research capacity and impact.
Minimum Qualifications
Bachelor's degree and a minimum of six (6) years of related experience; or any equivalent combination of education and experience.
Knowledge, Skills and Abilities

• Advanced knowledge of AI/ML methodologies and applications in health research
• Strong analytical, research design, and problem-solving skills
• Experience with grant writing and extramural funding processes
• Ability to lead interdisciplinary teams and training programs
• Strong communication and collaboration skills across technical and non-technical stakeholders
• Knowledge of data governance, reproducibility, and responsible AI practices

Preferred Qualifications

• Doctoral degree (PhD, ScD, DrPH, or equivalent) in data science, computer science, biostatistics, biomedical informatics, or a related field with significant AI/ML focus.
• Must be able to demonstrate experience applying AI/ML methods in biomedical, clinical, or public health research.
• Experience with grant development and interdisciplinary collaboration required.

Job Duties

• Lead and support AI/ML research initiatives across clinical, translational, and population health domains.
• Collaborate with faculty to integrate AI/ML methodologies into research projects.
• Contribute to study design, analytic strategies, model development, and validation.
• Develop and oversee AI/ML training programs for faculty, fellows, and students.
• Support development of grant proposals, including NIH and other federal funding opportunities.
• Contribute to scholarly publications, presentations, and dissemination of research findings.
• Facilitate collaborations across departments and with external partners.
• Promote best practices in data stewardship, reproducibility, and responsible AI.

Physical Requirements

• Communicating with others to exchange information.

Environmental Hazards

• No adverse environmental conditions expected.

Work Schedule
Monday-Friday, 8:00am-5:00pm
Driving University Vehicle
No
Security Sensitive
This is a Security Sensitive Position.
Special Instructions
Applicants must submit a minimum of two professional references as part of their application. If needed, additional references can be added after the application has been submitted.
Benefits
For information regarding our Benefits, click here.
EEO Statement
The University of North Texas System is firmly committed to equal opportunity and does not permit -and takes actions to prevent - discrimination, harassment (including sexual violence, domestic violence, dating violence and stalking), and retaliation on the basis of race, color, religion, national origin, sex, age, disability, genetic information, or veteran status in its application, employment practices, and facilities; nor permits race, color, national origin, religion, age, disability, veteran status, or sex discrimination and harassment in its admissions processes, and educational programs and activities. UNT System Administration promptly investigates complaints of discrimination, harassment, and related retaliation and takes remedial action when appropriate. System Administration also takes actions to prevent retaliation against individuals who oppose any form of harassment or discriminatory practice, file a charge or report, or testify, assist, or participate in a related investigation or proceeding.
Advertised: 04 Jun 2026 Central Daylight Time
Applications close:
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