Stellenbezeichnung: Internship / Thesis – Motion Prediction of Interacting Traffic Participants for Automated Driving using Machine Learning (m/f/d)
Arbeitsort / Location: München, Bayern – Ingolstadt, Bayern
Job Beschreibung: Internship / Thesis – Motion Prediction of Interacting Traffic Participants for Automated Driving using Machine Learning (m/f/d)
Internship / Thesis – Motion Prediction of Interacting Traffic Participants for Automated Driving using Machine Learning (m/f/d)
Student & Talent Programs
At CARIAD, it’s our mission to transform automotive mobility for everyone, everywhere, making it safer, more sustainable, and more comfortable in every way. To deliver on that promise, we’re building a unified technology and software platform, including a vehicle OS and cloud platform, as well as a unified architecture. As a 100% subsidiary of the Volkswagen Group, we’re developing solutions for all of its brands, including Volkswagen, Audi, and Porsche, and will bring our software to over 40 million vehicles by 2030.
Is this an easy task? Not at all! To tackle such a huge challenge, we need a great team. And that’s where you come in. You’ll join more than 6,000 CARIDIANS already working on the latest vehicle features and functions like automated driving, state-of-the-art charging technology, as well as a new digital ecosystem. Together, we’re bringing sustainable change to one of the largest companies in the world.
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 related to 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 student in computer science, data science, robotics or similar field
- Profound knowledge in machine learning, especially neural networks and reinforcement learning
- Proficiency in Python and deep learning frameworks (PyTorch, scikit-learn, Pytorch-Geometric)
- Nice to have: Experience in the field of Graph Neural Networks
- Analytical understanding of complex systems and problem solving skills
- Structured and independent work, above-average commitment and flexibility
- Fluency in both written and spoken English and German
NICE TO KNOW
- Duration: 6 months
- 35-hour week
- Remote work options
If you have further questions about the candidate journey at CARIAD, talk to Cari, our CARIAD Chatbot. Can’t see it? Check your settings or visit our
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