Master Thesis in Reinforcement Learning for Multiple-Embodiment Grasping

vor 3 Wochen


Renningen, Baden-Württemberg, Deutschland Robert Bosch GmbH Vollzeit
Master Thesis in Reinforcement Learning for Multiple-Embodiment Grasping

We are seeking a highly motivated and skilled Master's student to work on a research project in reinforcement learning for multiple-embodiment grasping.

Project Overview

The goal of this project is to design and implement architectures and pipelines for transferring current methods to online reinforcement learning algorithms. You will create reinforcement learning environments for multi-embodiment grasping using our grasp dataset generation pipeline and benchmark the current state of the art approaches in robotics grasping.

Responsibilities

  • Design and implement architectures and pipelines for transferring current methods to online reinforcement learning algorithms.
  • Create reinforcement learning 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 the research staff, who will guide you throughout your thesis.

Requirements

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

Additional Information

This thesis is a full-time position for 6 months. The requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

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



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