Associate Full Professor, Center for Applied Digital Health and Optimization Methods, Nutrition, Spring 2027

The College of Education Health and Human Sciences (CEHHS) at the University of Tennessee Knoxville invites applications for a 12-month Tenure-Track faculty position at the rank of Associate Professor or Full Professor. This individual will serve as the Associate Director of the new Center for Applied Digital Health and Optimization Methods led by Dr. Graham Thomas.

The Center for Applied Digital Health and Optimization Methods is designed to enhance the University of Tennessee Knoxvilles (UTKs) national footprint in digital health and optimization methods. The Centers work emphasizes the development and application of digital health technologies such as Just-in-Time Adaptive Interventions (JITAIs) wearable sensors and predictive analytics to address complex health challenges. This initiative leverages cutting-edge frameworks and methodologies including the Multiphase Optimization Strategy (MOST) Sequential Multiple Assignment Randomized Trials (SMART) Micro-Randomized Trials (MRTs) and control systems engineering approaches.

This position will join a diverse network of faculty across the College of Education Health and Human Sciences (CEHHS) and will serve as a catalyst for multidisciplinary collaborations within CEHHS and across colleges. The Center is dedicated to four primary foci:

1. Conducting and supporting externally funded research capitalizing on digital health;

2. Supporting multidisciplinary collaborations to bridge disciplines such as behavioral science and engineering;

3. Providing training in digital health and optimization methods as a part of undergraduate graduate and postdoctoral training programs;

4. Promoting the uptake of digital health and optimization methods in health research both locally and in the health sciences broadly.

This position carries a 12-month appointment with a primary faculty home in the merged Department of Nutrition and Public Health Sciences. Depending on the candidates background and expertise a joint appointment with another relevant department may be possible. The distribution of responsibilities is designed to ensure the successful leadership of the Center while maintaining a robust program of scholarly research and instruction:

Center Leadership (35%): The successful candidate will dedicate 35% of their effort to the leadership of the Center for Applied Digital Health and Optimization Methods as its Associate this capacity the individual will provide high-level strategic direction to support the official launch and foundational growth of the Center within CEHHS. A key priority for this role is identifying and cultivating opportunities for multidisciplinary research collaborations that capitalize on digital health and optimization methods across the university (e.g. with the Tickle College of Engineering College of Arts and Sciences College of Nursing). The Associate Director will provide instrumental support for the incorporation of digital health and optimization frameworks such as MOST SMARTs and MRTs into research studies and grant proposals to be submitted to funders such as the NIH and NSF that will be led by faculty across the college and university. The role also involves co-developing center-led training initiatives designed to enhance the proficiency of students at all levels as well as faculty in applied digital health and optimization science.

Research & Scholarship (30%): The candidate is expected to maintain an independent and impactful research program involving digital health and/or optimization methods. For example this may include applying frameworks and methodologies such as MOST SMART and MRTs or development and testing of just-in-time adaptive interventions (JITAIs) and wearable sensor technologies.

Teaching and Instructional Responsibilities (25%): Beginning in the second year of the appointment the successful candidate will provide high-quality instruction maintaining a standard 1:1 annual teaching load. Consistent with the Universitys commitment to research there may be opportunities for instructional buyout or teaching relief via externally funded research. Beyond formal classroom instruction a key component of this role involves providing mentorship to postdoctoral fellows within the Center for Applied Digital Health and Optimization Methods. Additionally depending on the candidates specific interests and the evolving needs of training programs there may be opportunities to mentor undergraduate and/or graduate students.

Service (10%): The successful candidate will have opportunities to provide service at the departmental college and university levels. This may include participation in faculty governance contributing to departmental and college-level committees and supporting the broader administrative goals of the University. Other forms of professional service may include cultivating industry partnerships participating in federal grant review panels and promoting the uptake of digital health and optimization methods within the broader scientific community.

This 12-month fulltime (1.0 FTE) position begins February 1 2027 and is negotiable. Starting salary is commensurate with experience. UTK has a competitive benefits package. The start-up package is based upon scholarship needs. UTK is Tennessees flagship land grant university and is currently in the midst of unprecedented growth in enrollment with approximately 38000 enrolled students. The University is also a Carnegie Foundation Research (R1) University with the highest research activity and has achieved a Carnegie Classification for Community Engagement.

We seek an established and recognized scholar whose work targets advancing health outcomes through the innovative application of digital health and/or optimization methods. Candidates must have earned their doctorate in psychology public health epidemiology biostatistics computer science engineering or a related discipline in the social behavioral or technical sciences. Candidates must meet the specific qualifications for these ranks as defined by the UTK Faculty Handbook. Candidates for the Associate Professor rank must have an established research agenda a strong record of scholarly activity and successful experience acquiring extramural funding (e.g. NIH NSF) as a lead investigator. Candidates for the Full Professor rank must demonstrate an extensive record of extramural funding as a lead investigator an extensive record of scholarly productivity and national/international recognition and proven experience in successful faculty mentoring and leadership within team science environments.

Preference will be given to candidates with a robust history of successfully applying and supporting the applied use of optimization methods such as the Multiphase Optimization Strategy (MOST) Sequential Multiple Assignment Randomized Trials (SMART) and/or Micro-Randomized Trials (MRT). Candidates with demonstrated experience in productive interdisciplinary collaborations successful team leadership and administrative experience in a research center environment are highly desired. Additional preferred qualifications include expertise in developing Just-in-Time Adaptive Interventions (JITAIs) the use of wearable sensor technologies experience with control systems engineering approaches and a proven history of cultivating successful industry partnerships to advance digital health research.