Key Responsibilities
- Research and develop reinforcement learning algorithms for humanoid robots
- Design and implement control policies for complex robotic movements
- Optimize RL algorithms for real-time performance on robotic hardware
- Collaborate with research teams to publish findings and contribute to open-source projects
- Develop simulation environments for training and testing RL policies
- Evaluate and benchmark RL algorithms against state-of-the-art methods
Requirements
- PhD in Robotics, AI, or related field with focus on RL
- 3+ years of experience in reinforcement learning research
- Proficiency in Python and deep learning frameworks (PyTorch/TensorFlow)
- Experience with humanoid robotics and control systems
- Strong publication record in top-tier robotics/AI conferences