Scholarship: Fully-funded
Degree: Bachelor, Master, Ph.D
Nationality: International Students
Location: USA
Application deadlines: Open
Scholarship Description:
The Computational Laboratory for Advanced Manufacturing and Sustainability (CLAMS) at Oklahoma State University was established by Professor Zheyu Jiang, who joined the Chemical Engineering Department in Fall 2021. CLAMS focuses on developing systems engineering solutions using mathematical modeling, optimization, big data, and machine learning to address interdisciplinary challenges such as industrial decarbonization, digital agriculture, and the Food-Energy-Water Nexus.
CLAMS is currently seeking 1-2 PhD students to work on multi-scale modeling, AI for Science, mathematical optimization, explainable AI, and safe reinforcement learning/optimal control in digital agriculture and clean energy system optimization. The expected start date is Fall 2025 or Spring 2026. Interested students are encouraged to inquire and apply.
For more information, please visit the CLAMS lab website: CLAMS Website.
Available Subjects:
- Systems Engineering, Applied Mathematics, and AI
Eligibility criteria:
- Although CLAMS is part of the Chemical Engineering Department, we invite applicants from interdisciplinary fields, including chemical engineering, industrial engineering, operations research, mathematics, and computer science.
- Applicants should have a strong mathematical foundation and be proficient in at least one scientific computing or programming language (e.g., MATLAB, Python, Julia, GAMS) and machine learning frameworks (e.g., PyTorch). A keen interest in mathematical modeling, optimization, and artificial intelligence research is essential.
- Applicants must have good spoken and written English skills. Proof of English proficiency can be demonstrated by official TOEFL, PTE Academic, or IELTS scores obtained within the last two years. The minimum requirements are TOEFL 79 iBT, PTE Academic 53, or IELTS Academic 6.5.
- Experience in areas such as partial differential equations, linear/nonlinear/integer/Bayesian optimization, or optimal control is a plus.
Application Procedure:
Please email [email protected] with your resume and transcript.
Shortlisted applicants will be invited for a mathematics background assessment, followed by an online interview. We will strive to minimize the overall application timeline and maintain communication throughout the process to ensure applicants have ample time to make decisions.
