Bachelor / Master Thesis – Moving Instance Segmentation using Machine Learning (m/f/d)

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.

YOUR TEAM

For the department Automated Parking we are looking for a thesis candidate for the project “Semantic instance segmentation in sparse radar point clouds using machine learning”. Our department works on innovative automated parking functions from the initial concepts, analyzing its requirements to securing its profitability and preparing the final approval. We are an open-minded and interdisciplinary team driven to bring our ideas to live – join our team!

WHAT YOU WILL DO

• Review literature of the current state-of-the-art algorithms and data sets
• Develop a method to reliably perform semantic instance segmentation
• Applied research on radar data using machine learning methods
• Test and validate the results on real world automotive data

WHO YOU ARE

• Enrolled student in the field of Computer Science, Electrical Engineering, Mechanical Engineering, Engineering Cybernetics, Mathematics or equivalent
• Know-how of relevant methods and algorithms from machine learning, point cloud processing, radar data processing or computer vision is a strong plus
• Very good programming knowledge and experience in Python
• Experience with common machine learning frameworks such as TensorFlow, PyTorch etc. is a strong plus
• Fluent in English
• High level of commitment, initiative and teamwork. Independent, goal-oriented and systematic way of working make you the ideal candidate

NICE TO KNOW

• Remote work options
• Duration: 3 to 6 months
• 35-hour week
• 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 FAQ

YOUR RECRUITING CONTACT

Sandra Neumeier

At CARIAD, we value individuality and diversity. We see great strength in our differences and can all benefit from the unique perspectives of others. We strive to employ people with diverse backgrounds who have the expertise, energy and focus to advance our mission. If you’re unable to submit an application because of a disability, please contact us at careers@cariad.technology.