Internship / Thesis - Scenario Generation for Autonomous Driving with Deep Generative Models (f/m/d) - #945216

We are CARIAD, the automotive software company of the Volkswagen Group. Our teams build automotive software platforms and digital customer functions for iconic brands like Audi, Volkswagen, and Porsche – supporting the Volkswagen Group in becoming the leading automotive technology company. With CARIDIANS in Germany, the USA, China, Estonia, and India, we are transforming automotive mobility for everyone.

Join us and be part of this exciting journey!

YOUR TEAM

To support our "ADAS/AD Predevelopment" team, we are currently looking for an intern or thesis student, searching for new solutions to cope with the current challenges in autonomous driving specifically in the field of simulation and virtual verification. Aiming at developing future assisted and automated driving, a key challenge to enable self-driving vehicles are artificial algorithms and the related handling (gathering, storing, processing) of vehicle mass data for various situations and use-cases.

What You Will Do

• Support one of our PhD students in the field of Generative Models for generating challenging scenarios for Autonomous driving
• Summarize research literature related to your research project
• Conduct research with SOTA methods on Scenario Generation to evaluate existing AV planners
• Develop algorithmic ideas addressing open research challenges related to your topic in the field of generative simulation for edge case driving scenarios leveraging models like diffusion
• Conduct comprehensive experiments on internal as well as public datasets
  
  

Who You Are

• Enrolled student in computer science, data science, robotics, electrical engineering or similar field
• Proficiency in Python and deep learning frameworks (PyTorch, scikit-learn, Pytorch-Geometric)
• Theoretical and practical experience in advanced machine learning and Generative AI – Generative Models - Diffusion models, transformers etc. is highly expected
• Experience in the field of reinforcement learning or implementations of popular research projects in the field is nice to have
• Analytical understanding of complex systems and problem solving skills
• Structured and independent work, above-average commitment and flexibility
• Fluency in written and spoken English
  
  

NICE TO KNOW

• Remote work options within Germany
• Duration for Intern: 6-8 weeks, followed by master thesis project
• 35-hour week
  
  

At CARIAD, we embrace individuality and diversity because we believe our differences make us stronger. We actively seek to build teams with a variety of backgrounds, perspectives, and experiences. Our goal is to create an environment where everyone feels valued and empowered to contribute. If you need assistance with your application due to a disability, please reach out to us at [email protected] - we are happy to support you.