Associate Professor/Professor of Data Science

Job Description

Job Description

Title: Associate Professor/Professor of Data Science

Employee Classification: Professor

Campus: University of North Texas

Division: UNT-Provost

SubDivision-Department: UNT-College of Information

Department: UNT-Data Science-133330

Job Location: Denton

Salary: Compensation is competitive and commensurate with the candidate’s qualifications, experience, and discipline, in accordance with university guidelines and available funding.

FTE: 1.00

Retirement Eligibility: ORP 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

Department Summary

The Anuradha and Vikas Sinha Department of Data Science at the University of North Texas is a rapidly growing research-driven department with strengths in data science, artificial intelligence, cybersecurity, software engineering, applied analytics, and emerging strength in quantum computing. The department is home to an active community of core faculty who lead externally funded research, collaborate with industry on cutting-edge projects, develop innovative curricula, and mentor students across undergraduate and graduate programs. Affiliated faculty from complementary disciplines further enrich the department’s interdisciplinary research environment and collaborative culture. The department offers a B.S. in Data Science, an M.S. in Data Science, and a PhD in Data Science.

Looking ahead, the department seeks to expand its research footprint and national visibility by recruiting faculty who are eager to build impactful, interdisciplinary research programs, secure external funding, expand industry collaborations, and contribute to the intellectual growth of a diverse student body. Future hires will play a key role in shaping the department’s research directions, fostering collaborations across the university and beyond, and advancing data-driven solutions to real-world societal challenges.

UNT has a highly diverse campus with a wide range of languages spoken in addition to English. We welcome candidates who have experience with HSI/MSIs and/or who speak Spanish, Vietnamese, American Sign Language, Chinese (Cantonese, Mandarin and other variations), Arabic, Tagalog, Farsi, French, or/and Yoruba.

Position Overview

The Anuradha and Vikas Sinha Department of Data Science at the University of North Texas invites applications for a tenured/tenure-track Associate Professor / Professor position in Data Science. The selected candidate will also receive the multi-year, renewable title of Reinburg Endowed Professor, subject to university policies.

This position is intended for candidates who seek to develop a high-impact, externally funded research program in a research-intensive (R1) environment and strong industry partnerships while contributing to excellence in teaching and service.

The standard teaching load for this position is two courses per semester during the regular academic year (2–2 load). Teaching responsibilities include undergraduate and graduate courses in data science and closely related areas, aligned with the candidate’s research expertise and departmental needs. Faculty are expected to demonstrate teaching innovation and effectiveness, mentor students, and contribute to curriculum innovation that integrates research and education.

The successful candidate is expected to establish and sustain a strong, independent research agenda, including the pursuit of external research funding from federal agencies, non-profit organizations and Foundations, and other sponsors, and the publication of research in high-quality, peer-reviewed venues. The candidate will also be expected to develop strong industry partnerships, engaging students in industry-relevant projects. Faculty members are expected to actively mentor graduate students, including supervising master’s theses and doctoral dissertations, and to engage in interdisciplinary research collaborations within the department, across the university, and with external partners.

In addition to research and teaching, the candidate will be expected to contribute to departmental, college, and university service, as well as leadership roles in the profession appropriate to the rank. The department values collaborative scholarship, interdisciplinary engagement, and research that addresses impactful, real-world data-driven challenges.

This position offers an opportunity to join a growing, research- and industry-oriented department and to contribute to its long-term vision of becoming a nationally recognized leader in data science research and graduate education.

As an endowed professor, the candidate is expected to have:
• established national or international scholarly reputation in Data Science, AI, or a related field.
• demonstrated record of external funding.
• research leadership, such as leading a lab, center, interdisciplinary initiative, major collaborative project, or large grant.
• professional leadership/service, such as editorial boards, conference leadership, professional societies, review panels, or similar activities.
• evidence of institutional impact, such as helping build programs, recruit students/faculty, expand partnerships, or raise research visibility.

Minimum Qualifications

1. An earned PhD in Data Science, Computer Science, Statistics, or a closely related field from an accredited institution by the time of appointment.
2. Demonstrated potential for high-quality scholarly research, as evidenced by peer-reviewed publications and strong research in progress in data science, machine learning, agentic AI, quantum computing, AI and/or related areas.
3. Demonstrated potential to establish an externally funded research program appropriate for a research-intensive (R1) institution.
4. Demonstrated ability or strong potential to teach effectively at the undergraduate and graduate levels in artificial intelligence, machine learning, data analytics, data governance, advanced research methods and closely related areas.
5. Demonstrated ability to develop and collaborate with industry partners on industry-relevant projects involving students.
6. Strong communication and interpersonal skills, with the ability to collaborate effectively with faculty, students, and interdisciplinary research teams.
7. Commitment to mentoring students, including undergraduate, master’s, and doctoral students, consistent with the expectations of a research-focused department.

Preferred Qualifications

1. Research expertise in Generative AI, including large language models, foundation models, prompt engineering, representation learning, post quantum cryptography and related areas.
2. Potential to secure external research funding in areas related to generative AI, or AI-driven data science from federal agencies, non-profit organizations and Foundations, industry, or other sponsors.
3. Experience or interest in interdisciplinary research, particularly applications of generative AI and quantum computing in domains such as health, cybersecurity, education, social sciences, or public policy.
4. Experience mentoring students or collaborating on research and industry projects, including supervision of graduate research or participation in multi-investigator teams.

Required License/Registration/Certifications

 

Physical Requirements

Communicating with others to exchange information.

Environmental Hazards

No adverse environmental conditions expected.

Work Schedule

varies based on assignment

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. Please provide up to 5 most important research publications

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.