MERL is looking for a highly motivated and qualified intern to work on deep learning for visual feedback in robotic manipulation. The ideal candidate would be a Ph.D. student with a strong background in deep learning and robotic manipulation. Several topics are available for consideration, including Object Pose Estimation, Goal-driven Grasping, Diffusion policy for Industrial Tasks, and Deformable Object Manipulation. The project requires the development of new algorithms with implementation and evaluation on a robotic platform. Preferred qualifications include experience working with a physics engine simulator like PyBullet, Isaac Gym, or Mujoco, proficiency in Python programming, and experience with ROS. The successful candidate will collaborate with MERL researchers, and publication of relevant results is expected. The start date is flexible, and the expected duration of the internship is 3-4 months. Interested candidates are encouraged to apply with their recent CV and a list of publications in related topics.
Research Areas: Artificial Intelligence, Computer Vision, Robotics.
Contact: Siddarth Jain.
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