In this program there will be a working experience in Deep Reinforcement Learning (DRL) particularly concentrated on control balancing. In the challenging task of sim-to-real transfer, interns will control our robotic manipulator as shown in Figure 1 that will hold a stable board position while a moving ball or water cup passes under it. Following on Taiwan Experience Education Program (TEEP), we are seeking to bridge theory and real-world application in the development of the next generation of robotic experts. In this regards, student might work with python, and Nvidia Isaac sim, gym, or Isaac lab along with ROS for different parts of robot control.