Assistant Professor - College for Health, Community and Policy, Kinesiology

About the Role

The University of Texas at San Antonio, College for Health, Community and Policy, Department of Kinesiology invites applications for a full-time Tenure-Track Assistant Professor position in Kinesiology with expertise in artificial intelligence (AI), data science, sports technology, robotics, or other areas of technology. The successful candidate will establish an active, interdisciplinary research program that secures external grant funding from federal or state agencies, private funding sources, or associations, while fostering collaborations within and outside Kinesiology, such as Engineering, Computer Science, Information Systems, Data Science, and Health Sciences. They may be asked to develop and teach a new course in AI or data science in Kinesiology and provide instructional support for existing Kinesiology curriculum including but not limited to Statistics, Evaluation, Exercise Physiology, Biomechanics, or Strength and Conditioning. This position will be provided the resources, mentorship, and infrastructure aligned with a tenure-track Assistant Professor role. Tenure is contingent upon Board of Regents' approval. This position will work primarily on campus. Travel and parking expenses are the employee's responsibility.

Responsibilities

• Establish an active, interdisciplinary research program in Kinesiology leveraging AI, data science, sports technology, robotics, or related technologies
• Secure external grant funding from federal agencies (e.g., NIH, NSF, DoD), state agencies, private funding sources, or associations
• Foster collaborations within and outside the Department of Kinesiology, including Engineering, Computer Science, Information Systems, Data Science, and Health Sciences
• Develop and teach a new course in AI or data science in Kinesiology
• Provide instructional support for existing Kinesiology curriculum, including Statistics, Evaluation, Exercise Physiology, Biomechanics, and Strength and Conditioning
• Maintain the security and integrity of UT San Antonio and its infrastructure per Texas EO-GA-48

Qualifications

• Doctoral degree in Kinesiology or a closely related field by the time of appointment (ABD candidates will be considered)
• Competencies in applying emerging technologies — such as AI, data science, sports technology, and/or robotics — to Kinesiology research
• Excellence in undergraduate and graduate teaching in Kinesiology, or evidence of teaching ability
• Ability to maintain the security and integrity of UT San Antonio and its infrastructure per Texas EO-GA-48

Preferred Qualifications

• An excellent scholarship record or strong potential for securing external funding from federal agencies (e.g., NIH, NSF, DoD) and private industry foundations
• Teaching credentials with specific capability to teach undergraduate and graduate courses such as Statistics, Evaluation, Exercise Physiology, Biomechanics, Strength and Conditioning, and a newly developed course in AI and data science in Kinesiology
• Relevant professional certifications (e.g., ACSM Exercise Physiologist, NSCA CSCS, ATC, or other relevant certifications)

Full-time, tenure-track position based primarily on campus at the University of Texas at San Antonio, College for Health, Community and Policy, Department of Kinesiology. Position contingent upon successful background check; verification of a valid driver's license and Motor Vehicle Record may be completed as applicable. Selected applicants must show proof of eligibility to work in the United States by time of hire.