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Cheoljoon Jeong

1 month ago

Industrial Engineering Clemson University in United States

I am recruiting fully funded PhD students in Industrial Engineering, Data Science, and AI at Clemson University.

Clemson University

United States

email-of-the@publisher.com

Dec 28, 2025

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Keywords

Computer Science
Data Science
Mechanical Engineering
Artificial Intelligence
Manufacturing Engineering
Industrial Engineering
Energy Engineering
Nonlinear Programming
Optimisation
Statistics
Statistic
Machine learning

Description

Clemson University is offering fully funded PhD positions in Industrial Engineering, starting in Spring or Fall 2026. These positions are based in the Industrial Data Science Lab, led by Dr. Cheoljoon Jeong, and focus on research at the intersection of data science, applied statistics, artificial intelligence, and nonlinear optimization. Research topics include AI-driven digital twins for manufacturing, IoT-enabled data science, and the integration of optimization and predictive modeling to improve efficiency and decision-making in engineering systems. Applicants should have a background in Industrial Engineering, Operations Research, Statistics, Machine Learning, Mechanical Engineering, or related fields, and be proficient in programming (Python or R). The program emphasizes interdisciplinary collaboration and offers a dynamic research environment with strong industry partnerships. Funding is fully provided, covering tuition and a stipend. To apply, candidates should email their CV, transcripts, and a research statement to Dr. Jeong. The application deadline is December 28, 2025.

Funding

These are fully funded PhD positions, covering tuition and providing a stipend. The exact stipend amount is not specified. Funding is provided for research in the Industrial Data Science Lab at Clemson University.

How to apply

Email your CV, academic transcripts, and a brief research statement to Dr. Cheoljoon Jeong with the subject line: 'Prospective PhD: [Your Name]'. Promising candidates will be invited for a virtual interview. For more details, visit the department website.

Requirements

Applicants must have a Bachelor’s or Master’s degree (completed or in progress) in Industrial Engineering, Operations Research, Statistics, Machine Learning, Mechanical Engineering, or a related field. Proficiency in programming and computational tools, particularly Python or R, is required. Candidates should demonstrate strong analytical and computational skills, a passion for research and innovation, and an interest in interdisciplinary research bridging data science, optimization, and engineering applications. Prior research experience in applied statistics, machine learning, or nonlinear optimization is advantageous but not mandatory. Strong communication and teamwork skills are expected.

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