Mehdi Hosseinzadeh

Washington State University is advertising a PhD opening in the Safe and Intelligent Autonomous Systems Lab (SIAS Lab) with Assistant Professor Mehdi Hosseinzadeh . The position is centered on control theory, optimization, robotics, autonomous systems, and learning-based control . The lab’s broader research includes safety, resilience, and long-term autonomy for autonomous cyber-physical systems, with application areas such as autonomous robots and vehicles, unmanned aerial systems, autonomous energy systems, video streaming platforms, and autonomous drug delivery systems. Ideal applicants should have a strong background in one or more of the following: control systems, robotics, optimization, machine learning, learning-based control, Python/MATLAB programming, ROS/ROS2, and experimental robotic systems . The post does not mention a specific funding package, stipend, tuition coverage, or deadline in the text provided. Applications must be submitted through the Google Form linked in the post. The announcer states that applications, CVs, or inquiries sent by email will not be considered , so candidates should use the form only. This opportunity is best suited to students interested in research at the intersection of robotics, autonomous systems, control, optimization, and machine learning at Washington State University.

Washington State University is advertising a PhD position in the Safe and Intelligent Autonomous Systems Laboratory (SIAS Lab) with Prof. Mehdi Hosseinzadeh . The research sits at the intersection of control theory , optimization , robotics , autonomous systems , and learning-based control . The lab’s broader research agenda focuses on the safety, resilience, and long-term autonomy of autonomous cyber-physical systems. Application areas mentioned on the lab page include autonomous robots and vehicles, unmanned aerial systems, autonomous energy systems, video streaming platforms, and autonomous drug delivery systems. This makes the opening especially relevant for students interested in robotics , electrical engineering , computer science , and mathematically grounded work in optimization and control . Ideal applicants should have a strong background in one or more of the following: control systems , robotics , optimization , machine learning , learning-based control , Python/MATLAB , ROS/ROS2 , and experimental robotic systems . The post does not mention a funding package, stipend, tuition coverage, or deadline. Applications must be submitted through the Google Form linked in the post. The announcement explicitly states that applications, CVs, or inquiries sent by email will not be considered, so interested candidates should use the form only.