Working Student

vor 1 Woche

Berlin, Deutschland CARIAD SE Vollzeit

Working Student - Data Acquisition and Self-Supervised Learning (M/F/d)

**AI / Data Platform**

**Student & Talent Programs**
- Berlin, Wolfsburg, Ingolstadt, Mönsheim/Stuttgart, Munich, Kassel

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**:
Our "Automated Parking" team is seeking a working student to collaborate on the project 'Data Acquisition and Self-Supervised Learning for Sparse Radar Data.' Our department is involved in developing innovative automated parking solutions, starting from initial concept development and requirement analysis, all the way to ensuring profitability and securing final approvals. We are an open-minded and interdisciplinary team, driven by our passion to bring our ideas to life. Join our team to get in touch with the world of autonomous driving and mobility within the VW group.

**WHAT YOU WILL DO**:

- Review literature of the current state-of-the-art algorithms and data sets
- Carry out data acquisition and integrate processing pipeline
- Test and validate the results on real world automotive data

**WHO YOU ARE**:

- Good academic performance.
- Enrolled student in the field of computer science, electrical engineering, mechanical engineering, engineering cybernetics, mathematics or equivalent field.
- Very good programming knowledge and experience in Python. Experience with common machine learning frameworks such as TensorFlow, PyTorch etc. is a strong plus
- Excellent English skills (oral and written). German would be beneficial.
- Proactive, team-player and results-oriented.
- Familiarity with machine learning, point cloud processing, radar data processing or computer vision would be a strong plus

**NICE TO KNOW**:

- Duration: 6 months
- 20 h/week, with the option to adjust to 35 h/week working model during semester break
- Start date: 01.01.2024

**YOUR RECRUITING CONTACT**:
Carmen Dörwald

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