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Associate Professor Computer Science Jobs in Oak Ridge, TN

Associate Director, Data Science

Knoxville, TN · On-site

$56K - $56K/yr

They are seeking an Associate Director of Data Science to lead their Data Science Team, focusing on ... D. degree in a relevant field such as Data Science, Statistics, Mathematics, Computer Science ...

Associate Director, Data Science

Knoxville, TN · On-site

$56K - $56K/yr

The Associate Director, Data Science will report directly to the Director, Data Science and should ... D. degree in a relevant field such as Data Science, Statistics, Mathematics, Computer Science ...

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Associate Professor Computer Science information

See Oak Ridge, TN salary details

$39.7K

$84.4K

$147.7K

How much do associate professor computer science jobs pay per year?

As of Jun 20, 2026, the average yearly pay for associate professor computer science in Oak Ridge, TN is $84,435.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,400.00 and $107,600.00 per year, depending on experience, location, and employer.

What opportunities for interdisciplinary collaboration are available to Associate Professors in Computer Science?

As an Associate Professor in Computer Science, you will often have the chance to collaborate with faculty and researchers from various departments such as engineering, medicine, business, and the social sciences. Many universities encourage interdisciplinary projects, allowing you to contribute your computing expertise to diverse research initiatives. These collaborations can enhance your research portfolio and open up new funding opportunities. Additionally, interdisciplinary work often leads to broader impacts and can help build professional networks both within and outside your institution.

What is the difference between Associate Professor Computer Science vs Assistant Professor Computer Science?

CriteriaAssociate Professor Computer ScienceAssistant Professor Computer Science
Required CredentialsPh.D. in Computer Science or related field, significant research and teaching experiencePh.D. in Computer Science or related field, typically early in academic career
Work EnvironmentUniversity faculty, research, teaching, service responsibilitiesUniversity faculty, research, teaching, service responsibilities
Employer & Industry UsageHigher academic rank, more responsibilities, often involved in departmental leadershipEntry-level faculty position, focus on establishing research and teaching

The main difference between Associate Professor Computer Science and Assistant Professor Computer Science lies in experience and rank. Associate Professors have more research, teaching, and service experience, often holding a higher academic rank with additional responsibilities. Assistant Professors are typically early-career faculty members working towards promotion. Both roles require a Ph.D. and are common in university settings, but the Associate Professor position signifies a more advanced career stage.

What does an Associate Professor of Computer Science do?

An Associate Professor of Computer Science is a mid-level faculty member at a college or university who teaches undergraduate and graduate courses, conducts research in computer science, and publishes scholarly work. They also supervise students, mentor junior faculty, and may participate in curriculum development and academic committees. In addition to teaching and research, Associate Professors often contribute to their academic community through service, such as organizing conferences or reviewing papers. Promotion to this rank usually follows demonstrated excellence in teaching, research, and service over several years as an Assistant Professor.

What are the key skills and qualifications needed to thrive as an Associate Professor of Computer Science, and why are they important?

To thrive as an Associate Professor of Computer Science, you need an advanced degree (typically a PhD) in computer science or a related field, with a strong track record in research, teaching, and publications. Familiarity with programming languages, learning management systems (such as Canvas or Blackboard), and research tools like MATLAB or Python is typically required. Excellent communication, mentorship, and collaboration skills help foster student engagement and interdisciplinary partnerships. These competencies are crucial for advancing research, delivering effective instruction, and contributing to the academic community.
What job categories do people searching Associate Professor Computer Science jobs in Oak Ridge, TN look for? The top searched job categories for Associate Professor Computer Science jobs in Oak Ridge, TN are:
What cities near Oak Ridge, TN are hiring for Associate Professor Computer Science jobs? Cities near Oak Ridge, TN with the most Associate Professor Computer Science job openings:
Associate / Full Professor, Center for Applied Digital Health and Optimization Methods, Nutrition...

Associate / Full Professor, Center for Applied Digital Health and Optimization Methods, Nutrition...

The University of Tennessee Knoxville

Knoxville, TN • On-site

Full-time

Posted 13 days ago


University Of Tennessee, Knoxville rating

7.1

Company rating: 7.1 out of 10

Based on 58 frontline employees who took The Breakroom Quiz

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Job description

Description
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 Knoxville's (UTK's) national footprint in digital health and optimization methods. The Center's 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 candidate's 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 Director. In 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 University's 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 candidate's 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 Tennessee's flagship land grant university and is currently in the midst of unprecedented growth in enrollment, with approximately 38,000 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.
Qualifications
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.
Application Instructions
Review of applications will begin on July 6, 2026, and will continue until the position is filled. Individuals interested in applying for this position should submit electronically at apply.interfolio.com/182795, and include a letter of application outlining how the candidate fits the qualifications and expectations of the position, curriculum vita, and list of three references who can address the applicant's capabilities with complete addresses, phone numbers, and email addresses. Questions can be directed to Dr. Hollie Raynor, search committee chair, at hraynor@utk.edu.

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