SAE Ground Vehicles Department is looking for an Assistant Instructor for the Robotics for Autonomous Vehicle Systems Bootcamp. Check out the information below and email us at [email protected] if interested.
Assistant Instructor – Robotics for Autonomous Vehicle Systems Bootcamp
Location(s): Warrendale, PA, Troy, MI or Remote
In this role, you would provide assistance to the lead instructor of this program as well as support for our learners for SAE International’s Robotics for Autonomous Vehicles Systems Bootcamp.
PRIMARY DUTIES AND RESPONSIBILITIES:
• Grade assignment submissions. Create an internal rubric to assess each submission against and provide feedback wherever necessary.
• Ensure the wordings of the assignments are up to date and all the latest commands and code are being sent to the students to work with, for their assignments.
• Maintain the class assignment repository on GitHub by pushing the necessary changes. Update the solution repository if needed.
• Provide individual support to each learner based on their needs.
• Provide support to the class on common doubts via TA sessions, Canvas discussion boards or Canvas Announcements as deemed fit.
EDUCATION and/or EXPERIENCE:
• Bachelor’s degree in CS, Robotics, Mechanical or other related areas.
• Master’s degree preferred in related areas.
SPECIALIZED KNOWLEDGE AND SKILLS:
• Proficient in ROS - Must know basics like publish subscribe, ROS networking, Gazebo, Rviz, ROS bags etc.
• Knowledge of the basics of how sensors used like RADAR, LiDAR and Cameras work.
• Understanding of robotics concepts like frames of reference, coordinate frame transforms and using tf and tf2 libraries in ROS.
• Command of control schemes like PID and formulation of control commands for longitudinal and lateral control.
• Good command in the usage of ML tools like Tensorflow, Keras and PyTorch. Should be able to work with pretrained models to implement object detection pipelines in ROS.
• Must be fluent with Git.
• Good command of the Linux system (Linux bash, file system).
• Knowledge of the ROS Navigation stack.
• Knowledge of and experience with the LMS Canvas.
• Fluent in C++ & Python.
• Good debugging skills.
• Knowledge of other generic geometric control schemes like Pure Pursuit, Stanley Control)
• Computer vision skills (basic knowledge of the OpenCV library).
• Knowledge of how SLAM packages like Hector, GMapping and Karto work in ROS (and in general too).
• Would be excellent if they have experience with the F1/10th platform.
• Knowledge of wheeled mobile robotics architectures and must be able to formulate kinematic equations of motion for differential drive and Ackerman steered vehicles.
• Proficient in code documentation.
• Ideally available at flexible hours to provide support to participants.