Master’s Research Opportunity in Multi-Robot Systems, Robotics, and Optimization at Georgia Southern University
The ARMOR Lab at Georgia Southern University, led by Assistant Professor Mingyu Kim, is seeking a highly motivated Master’s student to join cutting-edge research in multi-robot systems, autonomous robotics, and optimization. The lab’s research integrates rigorous theory with real engineering systems, focusing on near-optimal multi-robot operation under uncertainty, adaptive coordination with physical and communication constraints, predictive modeling using partial real-time sensor data, and robust decision making with experimental validation on robotic platforms.
Applicants should have a B.S. in Electrical and Computer Engineering, Electrical Engineering, Computer Engineering, Computer Science, or a closely related field. A strong background in mathematics (probability, optimization, linear algebra, control theory) and programming is essential. Experience with MATLAB, Python, or C++ and/or sensing and microcontrollers is expected. Prior research involvement, such as senior design, publications, or robotics projects, is highly valued. Admission to the ECE M.S. program at Georgia Southern University is required.
The position offers competitive funding packages, including tuition and stipend, based on qualifications and performance. Additional opportunities include high-impact publications, conference travel, and close mentorship in a fast-growing research lab. The ARMOR Lab provides a collaborative environment with access to modern labs and robotics facilities, and the university is a Carnegie Doctoral/R2 institution with engineering programs ranked in the top 15% nationwide.
Research in the ARMOR Lab spans multi-robot coordination and control, optimal sensor placement and network design, probabilistic modeling and state estimation, autonomous marine and aerial vehicles, and digital twin/data-driven modeling. Students will gain hands-on experience with ROS2, PX4, Python, MATLAB, C++, UAV/USV deployment, optimization, control theory, probability, and machine learning, as well as opportunities for collaboration with federal and state agencies and industry partners.
To apply, send your CV or résumé, transcript (unofficial is acceptable), and optional publications or project portfolio links to [email protected]. Applications are reviewed on a rolling basis, and early inquiries are encouraged. For more information, visit the ARMOR Lab website or contact Professor Mingyu Kim directly.