Job Responsibilities
1. Optimize tactile simulation models and utilize reinforcement learning methods to accomplish contact-rich dexterous manipulation tasks.
2. Establish efficient data collection and training pipelines, explore effective tactile representations, and employ imitation learning methods to achieve contact-rich dexterous manipulation.
3. Combine RL and IL to explore the use of tactile information in the field of robot-learning, explore methods to leverage tactile data for enhancing manipulation capabilities.
Qualifications
1. Ph.D. or higher in Computer Science, Robotics, Electronics, Mechanical Engineering, or related fields. Work experience is not mandatory but requires research project experience in robotics-related areas.
2. Solid foundation in Machine Learning, with in-depth understanding and hands-on experience in common models and training methods.
Preference will be given to candidates with project experience in reinforcement learning or imitation learning within the robot-learning domain.
