​We are seeking a highly motivated and innovative research intern to join our team and help us shape the future of robotics and artificial intelligence. The ideal candidate should possess a strong background in robotics, artificial intelligence, or a related field, with expertise in multi-agent RL, Social Navigation, Robot motion-planning, Game Theory and Model Predictive Control. Excellent problem-solving skills, a passion for innovation, and the ability to work effectively both independently and as part of a team are essential for success in this role.

​During the time of the internship, you are expected to:

• Explore and develop novel techniques in motion planning using expertise in reinforcement learning, game theory etc. with the focus on multi-agent robotic set ups in the field of social navigation.

• Implement these algorithms in a simulation environment and test against state-of-the-art baselines.

• Publish your research findings in top-tier conferences and journals.

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•     M.S./Ph.D. candidate in computer science, mechanical engineering, electrical engineering, or similar fields.

•     Proven experience in research and in developing algorithms for autonomous robot motion planning and task planning.

•     In-depth knowledge and practical experience in game theory, RL and Multi-agent RL.

•     Excellent programming skills in Python, C++.

•     Experience in modeling and simulating multi-agent systems using ROS or similar frameworks.

​•  Experience of working on the projects at the intersection of learning and control for multi-agent systems

•  Experience of working on the projects related to cooperative navigation.

•  Experience of working on the projects in the MARL setup

Multi-Agent RL, Social Navigation, Distributed decision making, Multi robot systems, Task Planning, MPC.