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  • MS/PhD Students
    Mechanical Engineering or Electrical and Computer Engineering
    Tennessee Technological University

    A Smart Manufacturing and Data Analytics Group (https://sites.google.com/site/smandda/ or https://scholar.google.com/citations?user=OJtZt_YAAAAJ&hl=en Tennessee Tech. Univ. is hiring graduate students for the Summer or Fall 2024 semester. Potential applicants (e.g., Spring 2025) can contact Dr. Duckbong Kim (dkim@tntech.edu) to discuss their interests and possibilities. Tuition, stipend for MS ($1600-1800/month), Direct PhD ($1800-$2000/month) and PhD ($1800-2200/month) student and travel for conferences will be financially supported.


    Our research group focuses on smart manufacturing and data analytics, such as industrial automation and robotics, XR:AR/VR/MR, additive manufacturing (AM), computational modeling, machine learning, and decision support. Among these, we are currently focusing on four main specific topics: 1) XR-based Smart Manufacturing, 2) Machine Learning and Computational Modeling, 3) Collaborative Robot, and 4) Machine Vision-based Digital Inspection Methodology (e.g., Cognex, PLC, and NI). For detail information, please visit the web-site of Smart Manufacturing and Data Analytics Group.


    Required background & knowledge: mechatronics, industrial automation and robotics, machine vision, numerical modeling, PLC, and programming (e.g., C++, Unity, and Python). Applicants should hold a baccalaureate or a master degree in a field of mechanical engineering, electrical engineering, computer science, industrial engineering or related-areas. Applicants may have earned a minimum of
    GPA: 3.0 on a 4.0 GPA scale (3.4 or the above preferred).
    GRE: Quantitative greater than 50%; Verbal greater than 33%; Writing greater than 33%
    TOEFL: 213 computer-based or 79 internet-based or can be replaced with TOEIC score.


    If you are interested in this study opportunity, please send your C.V. to Dr. Duckbong Kim (dkim@tntech.edu). We are looking forward to seeing highly motivated applicants for graduate study.


 


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