Applied Computing Jobs in Tennessee (NOW HIRING)

Description
The College of Emerging and Collaborative Studies (CECS) at the University of Tennessee, Knoxville's (UTK) seeks dynamic, collaborative, and innovative faculty members to contribute to its existing and future programs in Cybersecurity, Artificial Intelligence, Data Science, and Applied Computing. CECS has multiple positions across these disciplines open for non-tenure track, nine-month, full-time appointments beginning August 1, 2026. This is an open-rank search; appointment at the Teaching Assistant Professor, Teaching Associate Professor, Teaching Professor, or Professor of Practice level will be commensurate with qualifications and experience.
The selected candidates will be responsible for teaching and service, with assignments made by the dean according to enrollment demands and scheduling. Primary teaching responsibilities will include courses in emerging technologies such as Cybersecurity, Artificial Intelligence, Data Science, and Applied Computing, as well as other new courses launched by the College. We are seeking colleagues who bring deep applied expertise in one or more emerging technology domains and who share our commitment to education that is hands-on, intercollegiate, and workforce-relevant. Candidates are expected to maintain a scholarship focused on practice and impact; traditional academic research is welcome but not required.
Expertise in one or more of the following teaching areas is expected:
Applied Cybersecurity: network security fundamentals; penetration testing and ethical hacking; web application security; vulnerability assessment and management; intrusion detection and prevention; digital forensics and evidence handling; incident response; log analysis and threat detection; cloud security; and defensive and offensive applications of artificial intelligence in cybersecurity. As the graduate program launches, teaching responsibilities may expand to include advanced courses in red team operations, network forensics, security architecture, and enterprise risk management.
Artificial Intelligence: introductory artificial intelligence concepts and applications; natural language processing, programming techniques, and conversational AI; human-AI interaction and user experience design; AI ethics, legal frameworks, and social impact; AI-based data handling, preprocessing, and visualization; AI applications in cybersecurity; developing AI applications and AI-relevant programming in Python using frameworks such as Scikit-learn, TensorFlow, and PyTorch; and large language models (LLMs) and their APIs (such as OpenAI). As the graduate program grows, teaching responsibilities may expand to include advanced courses in machine learning, deep learning, generative AI, and computer vision.
Data Science: foundational data science concepts including data collection, management, and exploration; data stewardship, ethics, and lifecycle management; data storage, warehousing, and governance; analytical methods including statistics, machine learning, and optimization; advanced data analysis including multivariate regression, clustering, topic modeling, and time series analysis; data wrangling and preprocessing; visual analytics; programming in Python and R; data pipeline development and version control using tools such as GitHub and Jupyter notebooks; database design, SQL, and cloud-based data engineering; and communicating data science outcomes to technical and non-technical audiences. As the graduate program grows, teaching responsibilities may expand to include advanced courses in disciplinary applications of data science, scalable data engineering, and the legal, ethical, and societal implications of data-driven systems.
Applied Computing: foundations of computing, software development, databases, networking, DevOps, Cloud Computing, Web development, etc.
Key Responsibilities

• Teach undergraduate and graduate courses aligned with your area of specialization, including lab-intensive and applied learning components
• Develop and regularly update course materials to reflect current tools, frameworks, and industry practice
• Collaborate with intercollegiate program faculty to design integrative learning experiences that connect technical skills with ethical, policy, and real-world application contexts
• Advise and mentor students, including supervision of capstone projects and applied research
• Maintain an active applied scholarly or professional practice profile relevant to your specialization; traditional academic research is welcome but not required
• Contribute to program assessment, continuous improvement, and accreditation processes
• Participate in college governance, committees, and professional community engagement

Qualifications

• Teaching Assistant Professor - Holds a Ph.D. or terminal degree in a related field and must demonstrate clear potential for excellence in teaching core subjects and evaluation.
• Teaching Associate Professor - Ph.D or terminal degree with a proven record of effective college- or university-level teaching and evaluation.
• Teaching Professor (Full) - Ph.D or terminal degree with a sustained, consistent record of excellence and evidence of instructional leadership (e.g., curriculum development, mentoring, pedagogical innovation) commensurate with senior rank.

Preferred Qualifications

• Significant professional experience in a relevant industry or applied context (highly desirable)
• Relevant industry certifications, where applicable
• Record of applied scholarship: professional publications, conference presentations, tool development, vulnerability disclosures, or practice-based projects
• Experience developing or delivering simulation-based, lab-intensive, or capstone learning experiences
• Demonstrated ability or interest in teaching across disciplinary boundaries (e.g., cybersecurity and artificial intelligence, or cybersecurity and applied computing)
• Familiarity with curriculum development, program assessment, or accreditation processes (e.g., ABET, SACSCOC)
• Experience mentoring students from diverse backgrounds in technical fields

About the College:
The College of Emerging and Collaborative Studies (CECS) at the University of Tennessee, Knoxville, is at the forefront of changing the future of higher education. It is a first-of-its-kind college created to meet the needs of students seeking a customizable degree path in emerging fields such as artificial intelligence and data science that leads to rewarding careers upon graduation. CECS offers timely, innovative, student-centric degrees, minors, and stackable certificates at both undergraduate and graduate level that address the future talent gap and exposes students to experts and disciplines from across campus through cross-cutting curriculum. CECS utilizes strong industry partnerships to ensure students gain relevant skills and real-world experience, offering for-credit internships and multi-disciplinary projects. CECS emphasizes the cohort experience where students learn and interact with fellow students from across campus and disciplines, giving them the opportunity to learn from one another and work together to solve real-world problems.
The University of Tennessee, Knoxville is the state's flagship institution, a campus of choice for outstanding undergraduates, and a premier graduate institution. As a land-grant university, UTK is committed to excellence in learning, scholarship, and engagement with society.
Application Instructions
Priority will be given to applications received on or before June 1, 2026 via our Interfolio application system. (Link to Interfolio)
Applications must include:

1. a one-page cover letter addressing qualifications and motivation,
2. a teaching statement, including the candidate's background and experience that make them an ideal candidate, please include teaching evaluations if available.
3. a comprehensive curriculum vitae, and
4. the names and contact information (address, phone number, and e-mail address) for at least three professional references.

Questions about the position should be directed to CECS Senior Director of Academic Operations, Elis Vllasi, email: evllasi@utk.edu .
Positions to be filled as soon as possible.
To apply go to https://apply.interfolio.com/184890