Research in Management Science offers exciting opportunities to explore and enhance business processes in the fields of management science, operations management, logistics and transportation, using data analytics, statistics, mathematical modeling and optimization methods. Doctoral students in this concentration are rigorously trained to conduct scholarly research and to become outstanding teachers.
At Isenberg’s PhD program in Management Science, doctoral students receive an exceptional training under the tutelage of renowned faculty members. Their research is conducted at the highest levels of academic rigor and scholarly excellence and target prestigious journals of the field.
We support and prepare our students for exciting academic and research positions by offering:
The totality of the training and mentoring our students receive at Isenberg uniquely prepares them for outstanding careers.
Isenberg’s PhD in Management Science is a full-time, residential program designed to train students in the diverse area of management science and operations management. It comprises a solid program of coursework, a three-semester teaching requirement, and several examinations for the completion of the degree.
Management Science PhD students can study any area of interest and take courses in:
Isenberg faculty conduct research at the forefront of their disciplines and are involved in projects that are nationally and internationally funded by agencies such as the National Science Foundation.
In the management science program, students conduct novel research in such areas as supply chain management, manufacturing and service operations management, transportation and logistics, retail analytics, airline management, portfolio management, sustainable operations, humanitarian logistics and healthcare, quality management, or disruption and business continuity management, to name a few. Such research is methodologically grounded in management science core competencies and employs optimization theory, mathematical modeling, statistics, stochastic processes, and big data analytics.
Students are admitted for Fall semesters and receive an assistantship that is continued over four academic years (including their first three summers) subject to good academic standing and progress. Students complete forty-five credits of course work, in addition to a 3-credit teaching course. Admitted students are temporarily advised by the Ph.D. coordinator until their formally identify an advisor during their first or second semester. All students must have identified an advisor before their first summer. Students must successfully complete four examinations:
The Core Exam to assess a student's academic preparation for advanced work toward a Ph.D. degree.
The Comprehensive Exam, administered after the completion of a minimum of 36 credits of graded coursework.
The Dissertation Proposal Defense and the Dissertation Defense.
Here’s a sample of our required courses:
YEAR 1: Coursework and Core Exam
YEAR 2: Coursework and Comprehensive Exam.
YEAR 3: Development of dissertation proposal and Teaching
YEAR 4-5: Dissertation research, teaching and dissertation final defense.
