Open Rank in Mathematics in the ScAI Fall 2025

The ScAI cluster is part of the It takes a Volunteer cluster hiring initiative at the University of Tennessee Knoxville .

The ScAI Cluster will be a team of excellence in the science, mathematics, and optimization of AI for advancing scientific and engineering applications with a direct impact on additive manufacturing and hypersonics defense systems.

As part of this institutional priority initiative, new hires will join a dynamic core group of scientific collaborators with complementary experience and a shared interest in building a national reputation for excellence and innovation in ScAI.

In addition, members of the cluster are expected to work together to grow the University’s reputation in ScAI through shared grant proposals, publications, and innovative new curricular programming.

The new hires will also support and contribute to the AI TENNessee Initiative. The AI TENNessee Initiative is a new transdisciplinary research and education initiative focused on the State of Tennessee’s unique AI strengths and opportunities for innovation.

Led by the University of Tennessee, Knoxville, this initiative is engaging with academic, industrial, and community partners across Tennessee to leverage the benefits of AI across all disciplines and economic sectors in areas such as AI for science, smart manufacturing, climate-smart agriculture and forestry, precision health and environment, and future mobility.

• Our goal is to improve lives through AI research and education. The mission of the AI Tennessee initiative is to : 1) advance cutting-edge fundamental and transdisciplinary AI research and creative activity across all disciplines to address important challenges;
• 2) expand the number of Tennessee students developing skills and core competencies in AI across many disciplines to prepare them for AI-enabled jobs of today and the future;

and 3) partner with industry and institutions statewide to position Tennessee as a national and global leader in the data-intensive knowledge economy.

The University of Tennessee Knoxville is the flagship campus of the UT system, land-grant university, and a public Carnegie Research 1 institution.

As an 1862 land-grant university and as Volunteers, serving our state and nation is key to our mission. UT enrolls approximately 36,000 students at its Knoxville campus.

Under a united leadership across the UT system, university campuses, and colleges, UTK is undergoing transformational changes focused on solving some of the most audacious, pressing problems our country and world face today.

The city of Knoxville is a hidden gem surrounded by eight gorgeous lakes, with a beautiful and walkable downtown, a diverse music scene including internationally recognized festivals, active neighborhoods, unique restaurants, and a robust offering of diverse cultural and outdoor activities.

UTK is located within easy driving distance to the Great Smoky Mountains, Atlanta, Nashville, Asheville, Charlotte, Louisville, and Cincinnati.

It is only a day’s drive to Memphis, Chicago, and Washington, . Knoxville and the surrounding counties have a population of more than 850,000 people.

Minimum Qualifications

A PhD or equivalent degree in mathematics, applied mathematics, or statistics is required at the time of application.

Preferred Qualifications :

For an appointment at the Full Professor rank :

• Internationally recognized contributions and leadership in the Mathematics of Machine Learning, especially in the physics informed deep learning.
• Demonstrated exceptionally strong research publication record.
• Consistent track record for obtaining funding for the research programs, appropriate for the field of study.
• Leadership as a PI or co-PI, or participation as a Senior Personnel in interdisciplinary teams supported by an external source.
• Effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students, as well as postdocs.

For an appointment at the Associate Professor rank :

• Recognized contributions and potential for leadership in the Mathematics of Machine Learning, especially in the physics informed deep learning.
• Demonstrated highly strong research publication record.
• Potential for consistent track record for obtaining funding for the research programs, appropriate for the field of study.
• Potential for leadership as a PI or co-PI, or participation as a Senior Personnel in interdisciplinary teams supported by an external source.
• Effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students, as well as postdocs.

For an appointment at the Assistant Professor rank :

• Contributions in the Mathematics of Machine Learning, especially in the physics informed deep learning.
• Demonstrated strong research publication record.
• Potential for obtaining funding for the research programs, appropriate for the field of study. Potential for participation as a PI / co-PI / Senior Personnel in interdisciplinary teams supported by an external source.
• Effective, high-quality teaching skills, and ability to effectively mentor undergraduate and graduate students.
30+ days ago