Internship / Thesis – Motion Prediction of Interacting Traffic Participants for Automated Driving using Machine Learning (m/f/d)

vor 3 Wochen


Ingolstadt, Deutschland cariad Vollzeit

At CARIAD, we're bundling and further expanding the Volkswagen Group's software expertise. We’re uniting over 6,500 global experts to build a scalable technology stack, including a software platform, unified electronic architecture and reliable connection to the automotive cloud. Our CARIDIANS are developing vehicle functions such as driver assistance systems, a next-generation infotainment platform, power electronics and charging technology, and digital services in and around the vehicle.

Our software can already be found in Volkswagen ID. models and will soon power Audi and Porsche vehicles with the E3 1.2 platform in 2024.

It's no easy task, but with experts like you, we can shape the future of mobility. Join us at CARIAD and be part of this exciting journey

YOUR TEAM

We are a team of ambitious and highly motivated experts in the field of ADAS/AD innovation, searching for new solutions to cope with the current challenges in autonomous driving. 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 Scene Understanding and Motion Prediction
  • Study and summarize research literature on state-of-the-art approaches for your research project
  • Implement promising approaches in our software environment
  • Develop algorithmic ideas addressing open research challenges related to your topic
  • Conduct comprehensive experiments on internal as well as public datasets
WHO YOU ARE
  • Enrolled master's student in computer science, data science, robotics or a similar field
  • Profound knowledge in machine learning, especially deep neural networks
  • Proficiency in Python and deep learning frameworks (PyTorch, scikit-learn, Pytorch-Geometric)
  • Nice to have: Experience in the field of Graph Neural Network and Autoregressive Models
  • Analytical understanding of complex systems and problem solving skills
  • Structured and independent work, above-average commitment and flexibility
NICE TO KNOW
  • Duration: 6 months
  • 35-hour week
  • Remote work options
  • If you have further questions about the candidate journey at CARIAD, please contact us: 


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