Scholarship: Full award
Degree: BS, MS
Nationality: International Students
Application deadlines: Fall 2022
The dissertation research will focus on developing data-driven solutions for smart manufacturing. Statistical process monitoring, data mining, and machine learning will be intensively used in dissertation research. Specific topics may cover methodology innovation for manufacturing data processing and modeling, data-driven decision-making, interpretable or physics-informed machine learning, diagnostic and prognostics for advanced manufacturing processes (e.g., laser-based additive manufacturing).
You are welcome to apply if you are passionate about data and machine learning and interested in solving real-world decision-making challenges! Qualified candidates will be financially supported with full research assistantship.
Statistics, data analysis, and machine learning
- 1. Meet the admission requirement for the Ph.D. Program: https://poly.engineering.asu.edu/engineering/phd-systems-engineering/
- 2. Solid academic background in statistics, data analysis, and machine learning, e.g., undergraduate/graduate major in these areas, or have learned multiple courses related to the subjects.
- 3. Proficiency in coding (Python/R/MATLAB/C/C++/Java). Python is highly preferred. Linux experience is a plus.
- 4. Preferred major: statistics, applied mathematics, financial mathematics, industrial engineering, computer science, mechanical engineering, electronic engineering, civil engineering. Both graduate and undergraduates are encouraged to apply, but having a graduate degree is a plus.
- 5. Self-motivation, persistence, curiosity for knowledge, and willingness to learn
- Contact: [email protected], 480-727-5120
- Websites: https://isearch.asu.edu/profile/4001269