Position Overview

The Min H. Kao Department of Electrical Engineering and Computer Science (EECS) at The University of Tennessee, Knoxville (UT) is seeking candidates for one (1) tenure-track faculty position at either the assistant or associate professor level in computer science. The area of focus is Natural Language Processing (NLP) broadly defined, including AI areas such as Large Language Models and multimodal Generative Artificial Intelligence (GenAI). This search is to recruit a future leader on campus to lead basic research in GenAI and interdisciplinary research at the cross section of GenAI and vast amounts of healthcare records and diverse healthcare/biomedical applications. This search is part of the Precision Health and Environment Cluster Hire across multiple UTK departments.

Precision Health and Environment Cluster Hire

UT is searching for additional faculty to strengthen the university’s position as a global leader in Precision Health and Environment research; this position is among them and will begin August 1, 2026. Recruitment into Precision Health & Environment creates opportunities to build bold agendas that advance big ideas. The successful candidate will join a team of approximately 50 established and successful faculty with shared and complementary research interests in artificial intelligence (AI), health informatics, health information and communication, epidemiology, environmental engineering, systems modeling, natural language processing, and machine learning and a strong desire to grow the scholarly and educational impact of their work. For early career faculty, the cluster also offers a unique framework for professional development and mentorship within a rich transdisciplinary environment. Get more information about PHE.

The ideal candidate for this position has a collaborative mindset and prioritizes working with colleagues to realize shared research and educational achievements, including large-scale proposals, joint publications, and new transdisciplinary curricular programming. This unique opportunity may include joint appointments in other participating departments. As Tennessee’s flagship land-grant institution, UT is particularly interested in recruiting candidates who are deeply connected to the organizations and communities in which their work will have translational impact, as well as those who will contribute to a climate that values diversity and inclusion.

Researchers in the PHE cluster have additional collaboration opportunities through the UT Health Science Center, UT Medical Center, Tennessee Institute of Surgical Innovation, Institute for a Secure and Sustainable Environment, the Tennessee Water Resources Research Center, and the Baker School of Public Policy and Public Affairs. In addition, as the leading university partner in UT-Battelle, the management company for Oak Ridge National Laboratory (ORNL), UT offers extraordinary opportunities for cutting-edge research in science and engineering with the UT-Oak Ridge Innovation Institute (UT-ORII).

Through a streamlined IRB process, UT researchers have access to a unique rEDW (a research Enterprise Data Warehouse) system, which is a result of decade-long continued investment by UT. rEDW includes rich anonymized healthcare data, such as electronic health records (HER) on over 4 million patients, the associated medical imaging, digital radiology and pathology data, the associated location data for social determinants of health study, as well as genomics data on over 13 thousand children linked to EHR data for genotype-phenotype studies.

UT is the state’s flagship campus and leading research institution with a strong partnership with the nearby Oak Ridge National Laboratory (ORNL), where many UT faculty have ongoing joint positions and/or joint research projects. As a strategic investment, UT is leading the AI Tennessee, a research and education initiative by the State and the University to engage with academic, industry and community partners across Tennessee to leverage the benefits of AI across all disciplines and economic sections.

Required Qualifications

• PhD degree in Computer Science, Computer Engineering, or a related discipline at the time of appointment
• Effective, high-quality teaching skills
• Effectively mentor undergraduate and graduate students

For an Appointment at the Assistant Professor rank:

• Show potential for obtaining funding for the research programs
• Show potential for participation in interdisciplinary teams

For an Appointment at the Associate Professor rank:

• Expected to have conducted nationally/internationally recognized research works
• Show strong leadership potential

Preferred Qualifications

• Previous experience working in the convergent area of natural language processing, large language models, multimodal machine learning, and healthcare/biomedical applications.

Application Instructions

The application deadline is November 17, 2025. Applications received after the deadline may be considered until the position is filled. Please submit the following items online in Interfolio to complete your application:

• Cover Letter
• Curriculum Vitae
• Research Statement
• Teaching Statement
• Names and Contact Information of Three References

Apply Now