Northwestern University

Overview

The PhD in Industrial Engineering and Management Sciences at Northwestern University is designed to prepare researchers who leverage advanced methodologies to tackle significant challenges in various sectors, including industry, public policy, and healthcare. Students will cultivate a robust foundation in optimization, stochastic modeling, simulation, statistics, and data analytics, ultimately leading to careers in academia and industry.

What You'll Study

The curriculum is structured to enhance methodological expertise while fostering independent research. Coursework is aligned with research interests and prepares students for qualifying exams and dissertation milestones.

Indicative coursework areas include:

• Applied Mathematical Statistics
• Statistical Learning
• Stochastic Simulation
• Mathematical Optimization
• Stochastic Processes

Research and dissertation component:

• Doctoral research conducted under faculty supervision
• Development of a dissertation based on original contributions to the field
• Progress milestones, including qualifying and doctoral review steps, as required by the program

Common research themes include:

• Analytics and data-driven decision-making
• Optimization for operations and resource allocation
• Stochastic modeling for uncertainty and risk management
• Financial engineering and quantitative finance applications
• Logistics, supply chains, and healthcare operations
• Management science methods for organizational and policy decisions

Entry Requirements

Applicants should possess a bachelor's or master's degree in a relevant discipline. A prior degree specifically in industrial engineering is not a prerequisite. The program welcomes candidates from fields such as applied mathematics, computer science, economics, finance, mathematics, physics, statistics, and other engineering disciplines.

Career Prospects