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Xinchao Liu

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Fully Funded PhD Positions in Industrial & Systems Engineering (AI/ML, Digital Twins, Human-Machine Teaming) at Mississippi State University Mississippi State University in United States

Degree Level

PhD

Field of study

Computer Science

Funding

The positions are fully funded Ph.D. opportunities. No specific stipend amount or tuition coverage details are provided, but full funding is explicitly stated.

Deadline

Dec 28, 2025

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Country

United States

University

Mississippi State University

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Where to contact

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Keywords

Computer Science
Data Science
Systems Engineering
Mechanical Engineering
Aerospace Engineering
Mathematics
Artificial Intelligence
Non-destructive Testing
Industrial Engineering
Uncertainty Analysis
Statistics
Applied Mathematic
Digital Twins
Machine learning

About this position

Mississippi State University is offering fully funded Ph.D. positions in the Department of Industrial and Systems Engineering, supervised by Assistant Professor Xinchao Liu. The research areas include AI/ML-enhanced scientific and engineering modeling, digital twins, uncertainty quantification, optimal experimental design, and human-machine teaming in nondestructive testing. Students with backgrounds in industrial engineering, mechanical or aerospace engineering, statistics, applied mathematics, data science, computer science, or related fields are encouraged to apply. The positions are open for Fall 2026 or Spring 2027 entry. The academic environment at MSU is described as supportive, fostering both teaching and independent research. Funding is fully provided, though specific stipend and tuition details are not listed. Interested applicants should email their CV and transcripts to [email protected] with the subject line 'Prospective Ph.D. student: {Your Name}'. For more information, students can refer to the supervisor's LinkedIn profile. This opportunity is ideal for students interested in advanced topics such as artificial intelligence, machine learning, digital twins, uncertainty quantification, and human-machine collaboration within the context of industrial and systems engineering.

Funding details

The positions are fully funded Ph.D. opportunities. No specific stipend amount or tuition coverage details are provided, but full funding is explicitly stated.

What's required

Applicants should have a background in industrial engineering, mechanical or aerospace engineering, statistics, applied mathematics, data science, computer science, or related areas. Submission of a CV and transcripts is required. No specific GPA, language test, or other requirements are mentioned.

How to apply

Email your CV and transcripts to [email protected] with the subject line 'Prospective Ph.D. student: {Your Name}'. Applications are open for Fall 2026 or Spring 2027. Contact the supervisor directly for more information.

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