Teaching Faculty in Applied Artificial Intelligence

Description The College of Emerging and Collaborative Studies (CECS) at the University of Tennessee, Knoxville's (UTK) seeks a dynamic, collaborative, and innovative faculty memberto contribute to its existing and future programs in ArtificialIntelligence. CECS has one position open in Artificial Intelligencefor a non-tenure track, nine-month, full-time appointment, oncampus, beginning January 1, 2027. This is an open-rank search;appointment at the Teaching Assistant Professor, Teaching AssociateProfessor, or Teaching Professor level will be commensurate withqualifications and experience. The selected candidate will be responsible for teaching andservice, with assignments made by the dean according to enrollmentdemands and scheduling. Primary teaching responsibilities willinclude courses in Artificial Intelligence spanning introductorythrough graduate-level offerings, as well as other new courseslaunched by the College. We are seeking a colleague who brings deepapplied expertise in one or more artificial intelligence domainsand who shares our commitment to education that is hands-on,intercollegiate, and workforce-relevant. Candidates are expected tomaintain a scholarship focused on practice and impact; traditionalacademic research is welcome but not required. Expertise in the following teaching areas is expected: Artificial Intelligence: The College is especially interested incandidates whose primary strength lies in generative AI and largelanguage model engineering, agentic AI and multi-agent systems, AIsystems evaluation and safety, or AI forward deployed engineering —including retrieval-augmented generation, LLM fine-tuning, agentorchestration and tool use, prompt engineering, monitoring andevaluation of production AI systems (robustness testing,red-teaming, and hallucination detection), and the applied,client-facing deployment of AI solutions in real-world settings —as these are current strategic priorities for the program. Beyondthat focus, expertise is also expected in: introductory artificialintelligence concepts and applications; natural language processingand conversational AI; human-AI interaction and user experiencedesign; AI-based data handling, preprocessing, and visualization;and programming in Python using frameworks such as Scikit-learn,TensorFlow, and PyTorch. The ideal candidate will bring theknowledge and skills to teach courses such as Agentic AI andMulti-Agent Systems, Generative AI and Large Language ModelEngineering, AI Systems Evaluation and Safety, and AI ForwardDeployed Engineering, should the program choose to offer them inthe future. Key Responsibilities Teach courses spanning introductory through graduate level inArtificial Intelligence, including lab-intensive and appliedlearning components Develop and regularly update course materials to reflectcurrent tools, frameworks, and industry practice Collaborate with intercollegiate program faculty to designintegrative learning experiences that connect technical skills withethical, policy, and real-world application contexts Advise and mentor students, including supervision of capstoneprojects and applied research Maintain an active applied scholarly or professional practiceprofile relevant to your specialization; traditional academicresearch is welcome but not required Contribute to program assessment, continuous improvement, andaccreditation processes Participate in college governance, committees, and professionalcommunity engagement Qualifications Ph.D. in Artificial Intelligence, Computer Science, DataScience, or a closely related field Demonstrated expertise in one or more of the artificialintelligence teaching areas listed above Evidence of effective teaching at the university level, orsubstantial practitioner experience with instructional or mentoringresponsibilities Experience or demonstrated ability in the design and deliveryof courses in multiple formats, including face-to-face, synchronousonline, asynchronous online, and hybrid modalities Experience with technology-enhanced teaching and team-basedinstructional practices Commitment to applied, hands-on, and workforce-orientedundergraduate education Preferred Qualifications Significant professional experience in a relevant industry orapplied context (highly desirable) Relevant industry certifications, where applicable Record of applied scholarship: professional publications,conference presentations, tool or open-source software development,or practice-based projects Experience developing or delivering simulation-based,lab-intensive, or capstone learning experiences Demonstrated ability or interest in teaching acrossdisciplinary boundaries (e.g., applied AI and data science, orapplied AI and a domain application such as cybersecurity or healthdata) F amiliarity with curriculum development, program assessment,or accreditation processes (e.g., ABET, SACSCOC) Experience mentoring students from diverse backgrounds intechnical fields Faculty Rank Criteria Teaching Assistant Professor – Holds a Ph.D. (or will hold at the time of appointment) in a related field with promise forexcellence in teaching and related responsibilities, evidenced byearly effectiveness and contributions. Teaching Associate Professor – Terminal degree with a demonstrated record of excellence in teaching and relatedresponsibilities, with a minimum of three years of full-timeteaching experience in a related field. Teaching Professor (Full) – Terminal degree with a sustained,consistent record of excellence and evidence of instructionalleadership (e.g., curriculum development, mentoring, pedagogicalinnovation) commensurate with senior rank. Note: Applicants must be authorized to work in the UnitedStates. The college is unable to provide visa sponsorship for thisposition. About the College The College of Emerging and Collaborative Studies (CECS) at theUniversity of Tennessee, Knoxville, is at the forefront of changingthe future of higher education. It is a first-of-its-kind collegecreated to meet the needs of students seeking a customizable degreepath in emerging fields such as artificial intelligence and datascience that leads to rewarding careers upon graduation. CECSoffers timely, innovative, student-centric degrees, minors, andstackable certificates at both undergraduate and graduate levelthat address the future talent gap and exposes students to expertsand disciplines from across campus through cross-cuttingcurriculum. CECS utilizes strong industry partnerships to ensurestudents gain relevant skills and real-world experience, offeringfor-credit internships and multi-disciplinary projects. CECSemphasizes the cohort experience where students learn and interactwith fellow students from across campus and disciplines, givingthem the opportunity to learn from one another and work together tosolve real-world problems. The University of Tennessee, Knoxville is the state's flagshipinstitution, a campus of choice for outstanding undergraduates, anda premier graduate institution. As a land-grant university, UTK iscommitted to excellence in learning, scholarship, and engagementwith society. #J-18808-Ljbffr University of Tennessee, Knoxville