Deep Robotic Learning

Job Description

Robots in the future will not be programmed anymore, they will be able to learn, self-adapt and improve. One approach that could solve this problem is the use of Deep Reinforcement Learning (Deep RL). Reinforcement Learning enables the robot explore through trial and error, while looking for the optimal solution. Deep Learning help us handle unstructured environments and deal with the high dimensionality of the real world. We will explore and test different algorithms and learning technics that will enable robots to learn more robust, safer and faster. I am looking for highly motivated students that are open to learn the latest AI concepts and apply them in robotics.

Your Responsibilities

• Paper research for the latest state of art in Deep Robotic Learning
• Training and learning the robot in simulation, while testing different learning approaches
• Implementation of the trained data in simulation into real “hands on” robots

Our Offer

• An interdisciplinary working environment with partners from science, industry and society
• A working environment and organization close to business
• A pleasant working atmosphere
• Constructive teamwork

Your Profile

• Basic knowledge of C++ or Python
• Basic knowledge in machine learning, (optional OpenAI-Gym, TensorFlow, PyTorch)
• Self-reliant thinking and working
• Fluent in German or English
• Motivation and commitment

Application

We are looking forward to receiving your PDF application. Please send your application containing the following documents to Mr Atanas Tanev, tanev@fzi.de:

• Current transcript of records
• Curriculum vitae in tabular form

Job Description

• Start: as soon as possible
• Supervising institute at KIT: IAR - Institut für Anthropomatik und Robotik | Prof., Rüdiger, Dillmann