This is the department’s flagship graduate program and prepares the student for the rigorous demands of a career in research and development, or academia. It requires a strong background in mathematics, probability theory, optimization techniques and manufacturing systems. The PhD student is expected to be a full-time student. Although it is possible to seek candidacy as a part-time student, the PhD candidate must spend at least one academic year on campus full time. The graduate faculty typically works closely with individual doctoral students to create a flexible program tailored to individual needs.
Entrance to the PhD Program: To be admitted to the doctoral program, students must pass the PhD qualifying examination. The student must seek faculty approval to take this examination, which is typically given once a year in late April or early May and encompasses (1) Operations Research, (2) Probability, (3) Statistics & Data Analysis, (4) Manufacturing Systems & Basic Industrial Engineering, and (5) either Stochastic Processes or Micro & Nano Manufacturing. A cumulative grade point average of 3.30 or better in graduate course work and formal faculty approval are required in order to be able to take the exam. The examination allows the department to assess the student’s academic preparation and creative ability to conduct doctoral-level research. Students are expected to take the examination in April/May of the calendar year following the one in which they entered the graduate program, although it is acceptable to take the examination earlier.
Doctoral Course and Dissertation Credit Requirements: In addition to the basic core courses, doctoral students take additional courses that may be required in preparation for the PhD degree and the student’s dissertation topic. These courses are selected in conjunction with a program approved by the student’s advisor. According to University regulations, the PhD requires at least 72 credits beyond the bachelor’s degree or 42 credits beyond the master’s degree, including 18 credits for dissertation research. Currently, course credits typically include the following:
- Other required courses (IE 2100 , 2084 , 2088 ): 6-9 credits
- Qualifying core (IE 2006 , IE 2007 , IE 2072 , IE 2081 , IE 2011 OR IE 2084 ): 15 credits
- Additional course work (at least 6 credits of which must come from offerings outside the Department of Industrial Engineering): 21-24 credits
- Dissertation research (IE 3997 /IE 3999 ): at least 18 credits
Additional Doctoral Requirements: All full-time students must enroll in and attend IE 3095 (Graduate Seminar) each term they are in residence; the credits for these do not count toward the 72-credit requirement.
The comprehensive examination is taken by students after completing the course work in their concentration. The PhD comprehensive exam has a three-fold purpose: (1) to test the student’s proficiency (knowledge and skills) in his or her major area of interest; (2) to identify deficiencies in the student’s background and suggest remedial work; and (3) to test the student’s ability to prepare an acceptable dissertation in his or her area of concentration.
All doctoral students are expected to pursue research by working with individual faculty in areas that can lead to a potential doctoral dissertation. A PhD candidate must demonstrate the ability to conduct research of an original nature by completing a dissertation and preparing one or more papers of publishable quality. The dissertation topic is selected by the student in some theoretical or methodological area of interest in consultation with a faculty advisor. A faculty committee must approve the dissertation proposal before the student embarks on dissertation research. Information regarding the PhD program can be obtained by going to http://www.engineering.pitt.edu/Departments/Industrial/_Content/Graduate/Doctoral-Program/
Teaching Requirements for PhD Students: All PhD students should complete the following concentration in Scientific Communication, with two elements:
- Training program requires the completion of the following:
- Attendance at a minimum of one teaching workshop run by the Pitt Center for Integrating Research, Teaching and Learning (PITT-CIRTL) and approved by the department; see https://www.engineering.pitt.edu/cirtl
- Attaining a score of at least four in the ELI English Comprehensibility Test for TAs
- ENGR 2050 - TECHNICAL WRITING or ENGR 2052 - INTRODUCTION TO TECHNICAL COMMUNICATION
- Mentorship-in-practice: The goal of this requirement is to provide a mentored experience to the PhD students, regardless of their funding support, in classroom-based pedagogy. This requires one term as a TA and one term as an independent instructor. Satisfaction of this requirement, or any exceptions, must be approved by the graduate program director.