Working Student: Sim2real for Reinforcement
vor 3 Monaten
**What you will do**
Reinforcement learning (RL) has transformed robotics by enabling autonomous learning of complex tasks via trial and error. Yet, RL algorithms often require hundreds of thousands of real world training episodes, which can be difficult to obtain. To alleviate this, training is often done in simulation. However, successful transfer to the real world is also very challenging. Sim2Real transfer techniques aim to bridge the simulation-reality gap, enabling RL agents trained in simulation to generalize behaviors to real-world settings.
For this project, we are seeking a highly motivated student to join our research team as a Student Research Assistant. The primary focus of this position will be on Sim2Real transfer for reinforcement rearning in robotics. Your responsibilities will include:
- Setup of simulation environments for reinforcement learning agents
- Development of an experiment pipeline to deploy policies trained in simulation on real world robots
- Implementation of State-of-the art sim2real techniques
**What you bring to the table**
- Practical programming experience in Python and/or C++
- Hands-on experience in robotics
- Knowledge in deep learning and reinforcement learning
- Experience with ROS is a plus
Especially suitable for students with the field of study in Computer Science, Robotics, Electrical Engineering or similar.
**What you can expect**
- Participation in a dynamic team with innovative task areas
- Practical approach to your studies
- The flexibility to arrange your own working hours
- A laptop incl. headset
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.
Tom Haider
Fraunhofer Institute for Cognitive Systems IKS
Requisition Number: 72346 Application Deadline:
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