Master Thesis in Reinforcement Learning for Multiple-Embodiment Grasping: Designing Intelligent Systems

vor 2 Monaten

Renningen, Baden-Württemberg, Deutschland Robert Bosch GmbH Vollzeit
Master Thesis Opportunity in Reinforcement Learning for Robotics

**About the Project**

We are seeking a highly motivated and skilled Master's student to join our team at Robert Bosch GmbH and work on a challenging project in reinforcement learning for multiple-embodiment grasping.

**Key Responsibilities**

  • Design and develop architectures and pipelines to transfer current methods to an online RL algorithm.
  • Create RL environments for multi-embodiment grasping using our grasp dataset generation pipeline.
  • Benchmark the current state of the art approaches in robotics grasping.
  • Work under the remote and on-site supervision of our research staff, who will guide you throughout your thesis.

**Requirements**

  • Master studies in the field of Computer Science, Machine Learning, Artificial Intelligence, or a comparable field.
  • Proficient in Python, including best practices in code structure and packaging.
  • Machine Learning skills, including PyTorch, JAX, and TensorFlow.
  • Familiarity with physics simulators, such as MuJoCo, Bullet, or Isaac Sim.
  • High-level graphics libraries, such as Open3D, are a plus.
  • A goal-oriented person with a structured and analytical mindset.
  • Fluent in written and spoken German or English.

**What We Offer**

  • A dynamic and collaborative work environment.
  • The opportunity to work on a challenging project with a high impact on the field of robotics.
  • Professional development and growth opportunities.
  • A competitive compensation package.

**How to Apply**

Please submit your application, including your CV, transcript of records, examination regulations, and a valid work and residence permit, if required.

We are an equal opportunities employer and welcome applications from diverse candidates.

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