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Internship / Master Thesis - Driver Behavior Modeling for Automated Driving (m / f / d) - Inklusiver Job 🦼 🦻 🦯

CARIADIngolstadt, Bayern, DE

Vor 5 Tagen

Stellenbeschreibung

It's time to reshape automotive mobility for everyone!

At CARIAD, we have the mission to create and deliver leading digital technology for the Volkswagen Group. We're uniting over 6,000 global experts to build powerful software architectures that enable completely new customer experiences.

Iconic models like the Volkswagen ID. Buzz, Audi Q6 e-tron, and Porsche Macan 4 Electric are already equipped with CARIAD technology.

Join us at CARIAD and become part of an exciting journey to shape the future of mobility!

YOUR TEAM

To support our team for automated driving, we are looking for an intern or thesis student in the field of Machine Learning and Reinforcement Learning. In this role, you will gain hands-on experience in modeling driver behavior for automated driving using offline reinforcement learning and become an integral part of the team working on innovative solutions to the challenges of autonomous driving.

We are a team of ambitious experts in the field of ADAS / AD innovation, focused on developing artificial algorithms and efficiently processing vehicle mass data to advance assisted and automated driving. A key challenge is leveraging data from various driving situations to enable self-driving vehicles.

WHAT YOU WILL DO

Support one of our PhD students in the field of Behavior Modelling and Motion Prediction
Leverage Offline Reinforcement Learning for learning driver models
Study and summarize research literature related to your research project
Implement promising approaches in our software environment
Develop novel deep learning-based solutions for the future of automated driving
Conduct comprehensive experiments on internal as well as public datasets

WHO YOU ARE

Enrolled student in computer science, data science, robotics or similar field (please specify the expected date of your graduation or end of enrollment)

Profound knowledge in machine learning, especially neural networks and Reinforcement Learning

Proficiency in Python and deep learning frameworks (such as PyTorch, scikit-learn, Pytorch-Geometric)

Experience in the field of Graph Neural Networks and Offline Reinforcement Learning would be beneficial

Analytical understanding of complex systems and problem-solving skills

Structured and independent work, above-average commitment and flexibility

Fluent in both written and spoken English

NICE TO KNOW

Remote work options within Germany

Duration : 3 to 6 months

35-hour week

If you have further questions about the candidate journey at CARIAD, please contact us : [email protected]

YOUR RECRUITING CONTACT

Sandra Lehenmeier