Job Description
A research internship focused on applying reinforcement learning techniques to develop and optimize autonomous navigation capabilities for the ANYmal quadruped robot in industrial environments, involving simulation and real-world testing under mentorship from robotics experts.
Key Responsibilities
- Define, train, and integrate reinforcement learning models for robotic navigation.
- Evaluate and fine-tune RL-based navigation policies in simulation and on real robots.
- Contribute to advancing the mobility capabilities of the ANYmal robot.
Requirements
- Enrolled in a University and able to provide a supporting letter if a non-EU applicant, or a student enrolled at ETH or EPFL requiring a compulsory internship.
- Must reside in Switzerland (CH) or be eligible for a work permit if outside Switzerland.
- Must be available to start the internship at any time of the year, always on the 1st of the month.
- Must be able to commit to a full-time, 6-month internship with 100% workload, onsite.
- Must have a strong background in reinforcement learning techniques and simulation tools.
- Experience in evaluating and fine-tuning RL-based navigation policies in simulation and on real quadruped robots.
- Ability to work closely with robotics experts and research partners, demonstrating good collaboration skills.
- Must be able to define, train, and integrate machine learning models into robotic systems to enable safe and robust navigation in industrial environments.
Benefits & Perks
Full-time paid internship
Work on cutting-edge robot technology
Work with world-class experts and receive mentorship
Gain real-world experience in robotics and machine learning
Collaborative and dynamic work environment
Opportunity to contribute to impactful industrial applications
Onsite work environment
Internship duration of six months
Ready to Apply?
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