PhD Positions in Demonstration-Initialized Reinforcement Learning for Robotic Manipulation
Tasks
- Analyze experimental data and experimental design
- Build manipulation strategies for flexible objects
- Deploy learning based solutions on real robots
- Develop reinforcement learning initialized from human demonstrations
- Develop simulation models of robots sensors and components
- Integrate vision and tactile information into robot system
Perks/Benefits
- Access to state-of-the-art technology
- Collaborative research environment
- Onsite work
- Professional development opportunities
Skills/Tech-stack
Computer Vision | Data Analysis | Dynamics Simulation | Experimental Design | Reinforcement Learning | Robot Control | Robot Dynamics Simulation | Robot dynamics | Signal Processing | Simulation | Tactile sensing
Education
Roles
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