Amna Mazen

Fully funded PhD opportunity at Michigan Technological University in the Robotics and Remote Sensing Lab (RRSL) within the Applied Computing Department and the Department of Manufacturing and Mechanical Engineering Technology. The project focuses on industrial digital twins , with research interests spanning robotics , remote sensing , physics-based modeling , simulation , Python programming , sensor integration , IoT systems , and CAD/3D modeling . The student will work on modeling the behavior of physical systems and testing what-if scenarios. This opening is advertised as a Teaching Assistant position starting in Fall 2026 . Preference is given to candidates with experience in digital twins and current MTU students. Interested applicants should complete the linked form. For questions, contact [email protected] . Applications are reviewed on a rolling basis until the position is filled. Supervisors/lab leads mentioned on the lab page include Dr. Ashraf Saleem and Dr. Amna Mazen , both Assistant Professors at Michigan Technological University.

The Robotics and Remote Sensing Lab (RRSL) at Michigan Technological University is offering a fully funded PhD position in robotics, with a focus on machine learning and remote sensing. The lab, led by Assistant Professors Amna Mazen and Ashraf Saleem, specializes in areas such as autonomous robots, UAV-based remote sensing, computer vision, AI, mechatronics, and system integration. The successful candidate will join a dynamic research team working on cutting-edge projects that integrate robotic systems, advanced data acquisition, and AI-driven analysis to address real-world challenges. Applicants should have a strong academic background in robotics, computer science, engineering, or related fields, and demonstrate skills in programming, machine learning, and robotics. The position is fully funded, including tuition and a stipend as a Graduate Research Assistant. The application deadline is August 1, 2026, for a Spring 2026 start. Interested candidates should fill out the provided Google Form and review the lab's website for more information. For questions, contact the supervisors via email.