The Department of Mechanical and Industrial Engineering at the University of Massachusetts Amherst is inviting applications for fully funded PhD positions starting Fall 2026 under the supervision of Dr. Mengfan Xu, Assistant Professor. Dr. Xu is also affiliated with the Manning College of Information & Computer Sciences. Her research group focuses on online learning, sequential decision-making, multi-agent systems, robust learning under uncertainty, and simulation/data-driven optimization, with applications in supply chain management, trustworthy AI, cyber-physical systems, and security.

Research areas include multi-armed bandits, reinforcement learning, algorithm design, statistical learning, stochastic processes, and causal inference. The group aims to develop principled algorithms for dynamic, data-driven systems operating under uncertainty and interdependence, bridging theoretical rigor with practical impact.

Ideal candidates should have strong foundations in operations research, applied mathematics, computer science, or statistics, and possess strong analytical skills with creative proof abilities. Prior research experience in related areas is a plus. The group values curiosity, self-drive, and a genuine interest in learning and optimization in complex systems.

Funding for these positions is comprehensive, covering full tuition, competitive stipends, health insurance, and travel support. The application deadline is January 15, 2026, and applications are reviewed on a rolling basis until positions are filled. Selected candidates will be invited for a virtual interview, and final decisions are made by UMass Amherst via the formal graduate school application process.

To apply, prospective students should email their CV and a brief research statement to Dr. Mengfan Xu at [email protected], using the subject line 'Ph.D. Application – Fall 2026'. Formal applications must also be submitted through the UMass Amherst Graduate School portal, selecting the IEOR program and mentioning Dr. Xu's name in the application. For more information, visit Dr. Xu's academic webpage.

This opportunity is ideal for students interested in cutting-edge research at the intersection of operations research, machine learning, and optimization, with a supportive and dynamic research environment at a leading U.S. institution.