Doctor of Philosophy (PhD)
Tickle College of Engineering
The University of Tennessee, Knoxville, offers an online PhD in Industrial Engineering for practicing professionals seeking to gain the skills necessary to conduct research. Admission to the program requires at least an undergraduate degree with a relevant academic background.
48 with a master’s degree
72 without a master’s degree
Cost Per Credit Hour*
Asynchronous & Synchronous
Fall, Spring, Summer
*Cost per credit hour is an estimate based on maintenance and university fees. Some programs may have additional course fees. Please contact your department for additional information on any related fees, and visit Tuition and Fees in Detail at One Stop.
EARN YOUR DOCTORATE IN INDUSTRIAL ENGINEERING
The PhD in Industrial Engineering program is designed for working professionals interested in learning and performing research in any of the broad areas of industrial engineering. Our faculty do research in the areas of analytics, deep learning, and operations research and have a broad array of application areas such as health care, power systems, manufacturing, supply chain, and others.
Online learners are able to attend online classes in real time or watch the recordings. After finishing the course requirements, they will work directly with their advisors on their research topics of interest, with the expectation that the final PhD thesis will consist of three research articles that are publishable in respected peer-reviewed journals.
Students pursuing a PhD in Industrial Engineering will have the opportunity to take courses in diverse areas. Here are an examples of just a few:
IE 503: Research Methods in ISE
Introduction to basic research skills in Industrial Engineering, including literature review, research question identification and definition, scientific writing, paper revision, presentation, proposal development, network building, research ethics, and an overview of Industrial Engineering research methods.
IE 522: Optimization Methods in Industrial Engineering
Classical optimization applied to constrained and unconstrained, non-linear, multi-variable functions; search techniques; decision making under uncertainty; game theory; and dynamic programming.
IE 565: Applied Data Science
An introduction to applied data science including machine learning and data mining tools. Topics include supervised and unsupervised algorithms, techniques for improving model performance, evaluation techniques and software packages for implementation.
IE 560: Introduction to Proofs-Real and Convex Analysis
An introduction to real and convex analysis for engineers providing groundwork for optimization and probability theory. Topics include convergence, completeness, compactness, and continuity.
The PhD in Industrial Engineering offers two concentrations
Energy Science and Engineering
Courses include energy science and technology, environmental and climate science, grid management, biofuels, and more.
The engineering management concentration has an additional admission requirement of two years of relevant experience as a practicing engineer or scientist.
Ready to lead the way in Industrial Engineering?
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