Internship / Master Thesis - Self-supervised Learning of Time-series Data for Scenarios Identification (m/f/d)

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

Our "Data Analytics ADAS & AD" team is looking for an intern / master thesis student to develop state-of-the-art deep learning approaches addressing scenarios identification from time-series data within ADAS & AD.
We work on data analytics for verification and validation of ADAS functions. With large amount of collected data from test vehicle fleets, data becomes more important than ever for supporting the reliability and stability of ADAS & AD functions. We continuously analyzing the ADAS functions, identifying the corner cases and validating the performance of the systems.
You will collaborate and support our PhD student on their ongoing projects related to improving validation of ADAS functions. You get exposure of the best of both worlds in academia and practical projects. 

WHAT YOU WILL DO

• Review the state-of-the-art research literature
• Develop ideas addressing open research challenges related to the topic "self-supervised learning for time-series data"
• Conduct, document and design comprehensive experiments on internal as well as public datasets
• Implement ideas to identify different scenarios in latent space

WHO YOU ARE

• Enrolled student (or bachelor's graduate starting master's program as soon as possible) in the area of computer science, data science or equivalent field
• Proficiency in python and common deep learning framework (pytorch, mmcv, etc.)
• Strong skills in abstract and analytical thinking
• Experience in self-supervised learning, time-series data learning is a plus
• Fluent in English (oral and written)

NICE TO KNOW

• Remote options
• Duration: 3 to 6+ months 
• 35-hour week
• If you have further questions about the candidate journey at CARIAD, please contact us: y

YOUR RECRUITING CONTACT

Carmen Dörwald

Share this job offer