Ph.D. Student Position in Control Theory and Machine Learning for Networked Systems


   Department of Mechanical Engineering

  ,  Applications accepted all year round  Competition Funded PhD Project (Students Worldwide)

About the Project

About the position:

The groups of Dr. Wan and Dr. Sorrentino are jointly looking for one Ph.D. student who has a background in optimization, control systems, and machine learning. Our team is currently working on Learning-based Control for Networked Systems. Our joint mission is to integrate control theory and machine learning to solve practical problems in self-driving cars, unmanned aerial vehicles, and the safety and security of safety-critical systems.

Responsibilities:

The successful applicant will work with Dr. Wan, Dr. Sorrentino, and the wider research team. The primary role will involve conducting top-tier research and publishing the findings in esteemed conferences and journals, engaging in various team projects, interactive discussions, and workshops, and contributing to the academic community through seminars, peer reviews, and interdisciplinary collaborations.

Qualifications and Skills:

Applicants should possess a bachelor's or master's degree in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Computer Science, or a related field. They should exhibit proficiency in Julia, Python, MATLAB, or other programming languages and the ability to work in Linux-based high-performance computing environments. It would be a plus if students had some research experience or publications in related conferences or journals.

Required materials:

  • Inquiries are welcome to and . Please include CV/resume, a short write-up on statement of interests, and GRE scores.

Computer Science (8) Engineering (12)

Funding Notes

The position is fully funded for four years at the University of New Mexico, NM, USA.

Register your interest for this project


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