Rochester Institute of Technology
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Funded PhD in Optimization under Uncertainty for Supply Chain Management and Healthcare Operations Rochester Institute of Technology in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Funded 4-year PhD position.
Country
United States
University
Rochester Institute of Technology

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About this position
Funded PhD position at Rochester Institute of Technology in the Kate Gleason College of Engineering, Department of Industrial and Systems Engineering.
The project focuses on optimization under uncertainty with applications in supply chain management and healthcare operations. The work includes development and implementation of optimization models, research in operations research and optimization, and possible exposure to machine learning.
Students will work with Dr. Aliaa Alnaggar and benefit from interdisciplinary innovation, state-of-the-art facilities, and industry-oriented applications.
Eligibility: MS or BS (earned or to be granted) in Industrial Engineering, Management Science, Operations Research, Applied Mathematics, Operations Management, Information Systems, Computer Science, or a related field. Strong OR/optimization background and programming in Python, R, Java, C, or C++ are expected; Gurobi/CPLEX experience is a plus. Strong communication and self-motivation are important, and NSF REU / NSF GRFP experience is strongly encouraged.
Funding: 4-year funded PhD. Start date is Fall 2027, with Spring 2027 possible if already in the US. Review is rolling.
How to apply: email [email protected] with subject line Prospective PhD Student. Attach a CV, cover letter, references contact details, and sample papers/preprints if available.
Funding details
Funded 4-year PhD position.
What's required
MS or BS (earned or to be granted) in Industrial Engineering, Management Science, Operations Research, Applied Mathematics, Operations Management, Information Systems, Computer Science, or a related field. Strong background in operations research/optimization is required, along with programming skills in Python, R, Java, C, or C++. Gurobi or CPLEX experience is an asset. Strong communication and self-motivation are expected. NSF REU or NSF GRFP experience is strongly encouraged.
How to apply
Email [email protected] with the subject line "Prospective PhD Student". Include a CV, cover letter, references contact information, and sample papers/preprints if available.
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