Student Researcher in Computer Vision and AI

vor 4 Wochen


Böblingen, Baden-Württemberg, Deutschland Mercedes-Benz Vollzeit

Department: Research & Development

Specialization: Pattern Recognition

Company: Mercedes-Benz AG

Location: Mercedes-Benz Werk Sindelfingen

Join Us

Are you enthusiastic about the future of autonomous vehicles? We are seeking motivated students to become part of our research team focused on autonomous driving technologies.

Our projects aim to address the challenges faced by current sensors, such as stereo cameras and lidar, which can struggle in adverse weather conditions. Through initiatives like AI-SEE and nxtAIM, we are exploring innovative neural network architectures and sensor fusion techniques to improve sensor reliability and enhance object detection capabilities.

You will have access to substantial GPU resources and collaborate with an international team of experts. We also encourage a friendly atmosphere, where sharing a cake is part of our culture.

Qualifications

  • Pursuing a Master's degree in a quantitative field such as Computer Science, Physics, Mathematics, or Electrical Engineering.
  • Seeking a Working Student position or a Master's Thesis opportunity.
  • Fluency in English and/or German.
  • Strong programming skills in an object-oriented language like Python or C++.
  • Familiarity with Linux operating systems.
  • Ability to work independently and think critically.

Preferred Skills (not required)

  • Experience with deep learning frameworks such as TensorFlow or PyTorch.
  • Knowledge of Computer Vision, Foundation Models, and Generative AI.
  • Familiarity with Convolutional Neural Networks, Vision Transformers, or Diffusion Networks.
  • Experience in deep learning-based Object Detection, Depth Estimation, or Semantic Segmentation.

Additional Information

  • This position is based at our research lab.
  • We prefer candidates who can commit for a duration of six months.
  • For further inquiries, please refer to our contact channels.

Benefits

  • Meal allowances
  • Employee discounts
  • Employee participation options
  • Employee events
  • Coaching opportunities
  • Flexible working hours
  • Hybrid working options
  • Health measures
  • Pension plans
  • Mobility offers
  • Accessibility features
  • Good transport connections
  • Parking facilities
  • Childcare services
  • Company doctor
  • Cafeteria and café services


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