YOUR TEAM

This PhD position offers the opportunity to conduct research on end-to-end networks for automated driving within our AI Core team. The project explores joint optimization of the driving stack by training perception, prediction, and planning within a unified model architecture, with emphasis on efficient training strategies, closed-loop evaluation, reinforcement learning, and integration with predictive world models. Our department develops software and machine learning models for automated driving in urban environments. You will work alongside experts in autonomous driving and artificial intelligence, contributing to state-of-the-art research and production-oriented AI systems in an agile, research-driven environment.

WHAT YOU WILL DO

•    Conduct research in machine learning and AI for automated driving
•    Explore novel approaches for end-to-end automated driving systems, including imitation learning, reinforcement learning, and world models
•    Investigate scalable and robust training strategies for autonomous driving applications
•    Work with modern deep learning architectures and large-scale datasets
•    Prototype, implement, and evaluate machine learning models on public datasets and benchmarks
•    Contribute to scientific publications and present research results
•    Collaborate closely with interdisciplinary research and engineering teams
•    Contribute to the development of next-generation automated driving technologies

WHO YOU ARE

•    Excellent Master’s degree in Computer Science, Robotics, Mathematics, or a related field
•    Strong background in deep learning and modern machine learning methods
•    Solid understanding of computer vision, imitation learning, and reinforcement learning
•    Familiarity with world models, generative models, and autonomous driving is beneficial
•    Strong programming skills in Python, including PyTorch
•    Structured, independent, and research-oriented working style with above-average commitment
•    Strong communication skills and analytical understanding  
•    Very good English communication skills

NICE TO KNOW

• Duration: 3 years 
• Working with high ranked University 
• Remote work options 
• Possibility to supervise students 
• Temporary work from abroad in selected countries 
• 30 days paid leave 

Note: please upload your transcript of records 

If you have further questions about the candidate journey at CARIAD, please contact us: careers@cariad.technology 

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 careers@cariad.technology – we are happy to support you.