MERL is looking for a highly motivated intern to work on developing algorithms for robot learning using learning from demonstration, imitation learning and/or deep reinforcement learning. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publication. The candidate should have a strong background in (deep) reinforcement learning, Imitation Learning (or Learning from Demonstrations, LfD), machine learning and robotics. Prior experience of working with robotic systems is required. The candidate should be comfortable implementing the developed algorithms in Python and should have prior experience working with ROS. Prior exposure to deep learning and hands-on experience with packages such as Pytorch and/or Tensorflow is expected. The candidate is expected to be a PhD student in Computer Science, Electrical Engineering, Operations Research, Statistics, Applied Mathematics, or a related field, with relevant publication record. Expected duration of the internship is at least 3 months. The position is expected to be available starting late August or early September. Interested candidates are encouraged to apply with their recent CV with list of related publications and links to GitHub repositories (if any).
- Research Areas: Artificial Intelligence, Machine Learning, Robotics
- Host: Devesh Jha
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