University of Michigan

What you'll study

The PhD in Industrial Engineering (often housed within the Department of Industrial and Operations Engineering) combines rigorous coursework with sustained original research leading to a dissertation. Students take core classes in optimisation, stochastic processes and queueing theory, statistical learning and data analytics, systems modelling and simulation, and human factors/ergonomics, while selecting elective courses that align with their research focus.

• Core areas: mathematical optimisation and algorithms, stochastic modelling and simulation, statistical methods for systems, and research methods.
• Specialist topics: supply chain and logistics, manufacturing systems and automation, healthcare systems engineering, transportation and mobility, human–computer interaction and human factors, reliability and maintenance, and data-driven decision making.
• Research training: directed readings, advanced seminars, and participation in research groups and labs. Students develop a dissertation proposal, pass written and/or oral qualifying exams, and conduct original research under a faculty advisor.
• Teaching and professional development: opportunities to gain teaching experience as a graduate instructor or teaching assistant, plus workshops on grant writing, communication, ethics, and interdisciplinary collaboration.

Entry requirements

Applicants are expected to have a strong quantitative background typically demonstrated by a bachelor's or master's degree in industrial engineering, operations research, engineering, mathematics, statistics, computer science or a closely related field. Successful applicants commonly have substantial coursework in calculus, linear algebra, probability and statistics, and mathematical optimisation, plus evidence of research potential.

• Academic record: transcripts showing solid preparation in relevant mathematics and engineering subjects.
• Research experience: prior research, publications, technical reports or significant project work is highly valued and can strengthen an application.
• Application materials: a research statement outlining interests and potential faculty matches, a CV, letters of recommendation from academic or professional referees, and official transcripts. International applicants must meet the University's English language proficiency requirements.
• Faculty match: fit with faculty research areas is a critical factor; applicants should identify potential advisors and describe alignment in their research statement.

Career prospects

Graduates of the PhD programme move into a wide range of careers that leverage deep analytical and problem‑solving skills. Common trajectories include academic positions in engineering and operations research departments, research scientist or technical lead roles in industry R&D, and senior roles in operations, analytics, supply chain, manufacturing, and healthcare systems engineering. Graduates also join management and strategy consulting firms, government research laboratories, and technology companies where they develop and deploy advanced optimisation and data‑driven solutions.

Why study at University of Michigan

The University of Michigan offers a vibrant research environment with interdisciplinary centres and laboratories that complement industrial engineering research, including manufacturing and mobility initiatives, data science institutes, and health engineering collaborations. Students benefit from active research groups, access to experimental facilities and computing resources, and opportunities to work on real-world problems through partnerships with industry and public-sector organisations. Doctoral students are typically supported through research and teaching assistantships that provide mentoring, professional development, and close collaboration with established faculty leaders in the field.