"Open Rank Tenure Line Faculty in Artificial Intelligence, Machine Learning, and Data Science"

Open Rank Tenure Line Faculty in Artificial Intelligence, Machine Learning, and Data Science

Job Posting Number: 2026066TTL

The Ingram School of Engineering invites applications for a tenure-track faculty position at the ranks of Assistant Professor, Associate Professor, or Professor. This position is directly supported and motivated by the University’s Run to R1 strategic initiative, which seeks to elevate Texas State University to a “Very High Research Activity” (Research-1) status. The school’s priorities are fully aligned with the university’s Road to R1 goals, ensuring strong institutional support, access to advanced research infrastructure, and expanded opportunities for securing significant external funding.

Strategic Research Areas
The Ingram School of Engineering seeks to strengthen its research portfolio in Artificial Intelligence, Machine Learning, and Data Science, one of the university’s strategic research areas.
The successful candidate will be expected to:

• Increase the research capabilities of the Ingram School of Engineering in Artificial Intelligence, Machine Learning and/or Data Science.
• Demonstrate a strong commitment to student-centered teaching and mentorship at both undergraduate and graduate levels.
• Collaborate with faculty across the Ingram School of Engineering, the College of Science and Engineering, and other Texas State departments.
• Contribute to curriculum and program development.
• Build partnerships with external stakeholders, including industry professionals, government agencies, national labs, and corporations.
• Engage in university and professional service and participate in shared governance of the school.
• Possess expertise in one or more of the following research areas:

AI, Machine Learning and/or Data Science for Mechanical and Manufacturing Systems
Including AI-enabled digital twins, generative design, structural health monitoring, predictive maintenance, robotics, human-robot interaction, and advanced manufacturing.

AI, Machine Learning and/or Data Science for Quality Control and Process Analytics
Leveraging computer vision, real-time sensing, data analytics, and edge computing for manufacturing quality and efficiency.

AI, Machine Learning and/or Data Science for Supply Chain and Industrial Optimization
Focused on smart, sustainable logistics networks, demand forecasting, inventory management, transportation optimization, and process improvement.

AI, Machine Learning and/or Data Science for Communications and Computing
Covering next-generation wireless systems, RF technologies, neuromorphic and edge computing architectures, passive RF sensing and energy-efficient AI acceleration.

AI, Machine Learning and/or Data Science for Emerging Technologies
Such as quantum control systems, hybrid quantum-classical algorithms, and AI-assisted optimization for energy systems.

About the Ingram School of Engineering:Founded in 2007 through generous endowments from the Ingram family, the school is dedicated to delivering exceptional education and advancing cutting-edge research across multiple engineering disciplines. We offer Bachelor and Master of Science programs in Civil, Electrical, Industrial, Manufacturing, and Mechanical Engineering, as well as three newly launched Ph.D. programs in Civil Engineering, Electrical Engineering, and Mechanical/Manufacturing Engineering. These doctoral programs emphasize Artificial Intelligence and Disruptive Technologies, innovation, and commercialization. Faculty also contribute to the multidisciplinary Materials Science, Engineering, and Commercialization Ph.D. program within the College of Science and Engineering. Our dynamic environment has contributed to significant enrollment growth, resulting in a doubling of undergraduate and graduate student numbers within the past few years.Our culture emphasizes student-centered learning, multidisciplinary collaboration, and community engagement, preparing graduates for leadership roles in engineering and research. Faculty are doing transformative research in key areas of impact, including AI & machine learning, Industry 4.0 and smart manufacturing, renewable energy, semiconductors, technology enhanced infrastructure, transportation, and water resources, among others.The school has excellent laboratory facilities and centers that foster collaboration and innovation:

• Infrastructure Research Laboratory (IRL): A $15M state-of-the-art facility for large-scale geo-structural and material testing.
• Ingram Makerspace: A hands-on innovation hub equipped with 3D printers, CNC machines, laser cutters, and electronics workstations for advanced prototyping and entrepreneurial initiatives.
• USDOT Tier I University Transportation Center (CREATE): Focused on coastal infrastructure durability and resilience, including water resources and extreme events.
• NSF CREST Phase I Center for Ultrawide Bandgap Semiconductor Device Materials: Advancing semiconductor technologies for next-generation applications.
• Access to university-level centers and shared research operations, including the Meadows Center for Water and the Environment and the Center for Analytics and Data Science (CADS).

Texas State University is strategically located in San Marcos, Texas, in the heart of the Austin-San Antonio corridor, one of the fastest-growing and most dynamic regions in the United States. This prime location provides unparalleled access to a thriving technology and innovation ecosystem in Austin, home to major tech companies, startups, and research hubs, as well as strong connections to San Antonio’s industrial, manufacturing, and defense sectors. Faculty and students benefit from proximity to industry leaders, enabling collaborative research, internships, and partnerships that drive innovation and economic impact.

To assure full consideration, applications must be submitted by January 15, 2026.

Required Qualifications

At the Assistant Professor Level:

• An earned doctorate in civil engineering, electrical engineering, industrial engineering, mechanical engineering, manufacturing engineering, or a closely related discipline.
• Evidence of or potential to obtain eternal funding and/or corporate gifts.
• Evidence of or potential for research excellence in one or more of the research areas mentioned above.
• Evidence of or potential for excellence in teaching both graduate and undergraduate courses in ABET Accredited engineering programs, including lectures and laboratories.
• A history of or potential for advising student projects.
• Demonstrated excellence in written and oral communication.

At the Associate Professor Level:

• An earned doctorate in civil engineering, electrical engineering, industrial engineering, mechanical engineering, manufacturing engineering, or a closely related discipline.
• Evidence of having obtained eternal funding and/or corporate gifts.
• Evidence of research excellence in one or more of the research areas mentioned above.
• Evidence of excellence in teaching both graduate and undergraduate courses in ABET Accredited engineering programs, including lectures and laboratories.
• A history of advising student projects at both the undergraduate and graduate levels.

At the Professor Level:

• An earned doctorate in civil engineering, electrical engineering, industrial engineering, mechanical engineering, manufacturing engineering, or a closely related discipline.
• Evidence of an established and current funding record of obtaining eternal funding and/or corporate gifts.
• Evidence of a nationally and internationally recognized research agenda and a publication record with contributions in one or more of the research areas mentioned above.
• Evidence of excellence in teaching both graduate and undergraduate courses in ABET Accredited engineering programs, including lectures and laboratories.
• A history of advising student projects at both the undergraduate and graduate levels.
• Evidence of an established reputation, leadership and service at the national and international levels.

Preferred Qualifications

At the Assistant Professor Level:

• Evidence of or potential for interdisciplinary research collaboration.
• Industrial, or post-doctoral experience (in an area of expertise that complements those of the department faculty).

At the Associate Professor Level/Professor:

• Evidence of interdisciplinary research collaboration.
• Knowledge of ABET accreditation procedures and related deliverables.
• Evidence of establishing partnerships with national labs and government agencies.
• Evidence of submitting invention disclosures, obtaining patents, and managing intellectual property.

Open Until Filled? Yes

Quicklink: https://jobs.hr.txstate.edu/postings/55413

For a detailed description of this position and to apply, visit https://jobs.hr.txstate.edu/postings/55413 or call (512) 245-2557 or visit our office at 601 University Dr., J.C. Kellam Bldg., Suite 340.