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Internship/ Master Thesis- Foundation Models for Detection of Unknowns in Visual Perception (m/f/d)

It's time to reshape automotive mobility for everyone!
At CARIAD, we have the mission to create and deliver leading digital technology for the Volkswagen Group. We're uniting over 6,000 global experts to build powerful software architectures that enable completely new customer experiences.
Iconic models like the Volkswagen ID. Buzz, Audi Q6 e-tron, and Porsche Macan 4 Electric are already equipped with CARIAD technology.
Join us at CARIAD and become part of an exciting journey to shape the future of mobility!

YOUR TEAM

Our "Visual Perception" team is looking for "intern/ working student/ thesis" to support us. We are a small team of 6 employees, with the focus on innovation technologies and getting the innovation realized by prototype setups e.g. in a vehicle.
The team is working in with an agile project setup with the spirit to "get things done".
Even we are a small team, we are at 3 locations and therefore established a good way of working remote and align in virtual meetings, For sure to get the prototype up and and running we meet and work in the garage.

WHAT YOU WILL DO

  • Collaborate and support our PhD students on a variety of projects within the field of Visual Perception
  • Analyse and present research literature related to your research project
  • Implement and extend promising approaches in our software environment
  • Develop algorithmic ideas addressing open research challenges related to the topic "foundation models/generative models for detecting unknowns in visual perception"
  • Conduct, document and design comprehensive experiments on internal as well as public datasets


WHO YOU ARE

  • Enrolled student in computer science, data science, robotics or equivalent field
  • Structured and independent work, above-average commitment and flexibility
  • Profound knowledge in machine learning, especially deep neural networks
  • Proficiency in Python and deep learning frameworks (PyTorch, OpenCV, scikit-learn)
  • Analytical understanding of complex systems and problem-solving skills
  • Fluent in English
  • Experience in object detection, semantic segmentation and/or foundation models in computer vision would be beneficial


NICE TO KNOW

  • Remote work options
  • Internship
    • Duration: 3 to 6+ months
    • 35-hour week
  • Working Student
    • Duration: 6 months
    • 20 h/week, up to 35 h/week during semester break
  • If you have further questions about the candidate journey at CARIAD, please contact us: careers@cariad.technology



YOUR RECRUITING CONTACT

Sandra Lehenmeier

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Internship/ Master Thesis- Foundation Models for Detection of Unknowns in Visual Perception (m/f/d)

Ingolstadt
München
Home Office, Praktikum / Werkstudent:in

Veröffentlicht am 13.11.2024

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