Internship / Thesis Robotic Foundation Models for Automotive Final Assembly (m / f/d)

Description

Robotik in der Fertigung, Transformation Fertigung, Künstliche Intelligenz What we offer Depending on qualifications and professional experience, the annual gross salary for this position for a 35-hour week can range from [min. annual gross salary of the corresponding TB in EUR] to [max. annual gross salary of the corresponding TB in EUR; usually ES 20]. If particularly suitable, a gross annual salary of up to [Max. Annual gross salary of the corresponding TB in the Plus pay scale in EUR; usually ES 25] is possible. Contact person for this posting: Team Volkswagen AG Studierende & Doktoranden Robotik in der Fertigung, Transformation Fertigung, Künstliche Intelligenz

Company

• Volkswagen AG

Contract

• Fixed-term

Department

• IT and Digitalization

Shift

• Full-time

Experience

• Interns

Qualification requirements

• Master's students in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a comparable field

• Very good to good academic achievements

• Strong analytical and conceptual skills as well as familiarity with scientific methods

• Ability to work independently as well as in interdisciplinary teams, high motivation

• Good knowledge of machine learning and neural networks as well as practical experience with PyTorch in research projects

• Solid programming skills in Python and basic knowledge of Linux

• Ideally experience with ROS / ROS 2, robot simulations (e.g. Isaac Sim, MuJoCo, Gazebo) or fundamentals of robotics

• German or English at proficiency level C1

Brief Role Description

• As part of the Group IT for Production and Logistics, we are responsible for software deployed across the entire process chain and are actively shaping the transformation toward AI-supported, data-driven production. Our team conducts research at the intersection of industrial robotics and modern AI methods with the goal of bringing autonomous systems into real manufacturing environments.As part of your internship (minimum 6 months) or thesis, you will explore how modern learning-based approaches can meet the specific requirements of automotive final assembly, ranging from data collection to the evaluation of real manipulation tasks. If you are pursuing a master's thesis, the task definition and research questions will be determined together with your supervising professor after confirmation of supervision. Your results will directly contribute to the development of the next generation of autonomous assembly systems. We look forward to your application.

Possible Tasks within this Role

• Setting up and commissioning collaborative robots and sensor systems in an experimental research environment

• Researching and analyzing current literature on learning-based methods for robotic manipulation

• Practically investigating data-driven deep learning approaches for controlling real robot systems for a selected use case in automotive final assembly

• Collecting, structuring, and evaluating demonstration data under industrial conditions

• Assessing the performance of trained models based on self-developed or predefined evaluation criteria

• Documenting and presenting results

Folgende Dokumente sind mit der Bewerbung einzureichen

• Anschreiben + Lebenslauf

• Aktuelle Immatrikulationsbescheinigung

• Aktueller Notenspiegel

• Bei einem Pflichtpraktikum zusätzlich eine Bescheinigung der Hochschule

• Arbeitserlaubnis für Nicht-EU Bürgerinnen / Bürger