In this program, the students need to work on our (a) physical robot and (b) Deep Reinforcement Learning (DRL) algorithms to get experience and solve problems with dual-arm robots. In the challenging task of sim-to-real transfer, interns will control our robots as shown in Figure 1, which will manipulate sensitive objects under self-balancing mode. Following the excellent Taiwan Experience Education Program (TEEP), we are aiming to bridge theory and real-world application in the development of state-of-the-art robotics systems and a new generation of robotic experts. In this regard, our student will work with Python, state-of-the-art Nvidia Isaac Sim, and Isaac Lab. They also focus on the ROS 2 control system for applications where they need to control the robot.