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CA
CARIAD SE
7d ago

Internship / Master Thesis - End-to-end Automated Driving with World Models(m/w/x)

München
from 13.9 / hour
Full-timeInternshipWith Home Office

Description

In this role, you will advance automated driving by researching neural networks and world models. You'll collaborate with experts to conduct experiments that aim for a meaningful scientific contribution.

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Requirements

  • Master student in Computer Science, Robotics, Electrical Engineering or similar
  • Knowledge in (self-)supervised learning, transformer-based architectures, and foundation models
  • Knowledge of PyTorch, software development, Python, and C++
  • Structured work, commitment, and flexibility
  • Strong communication skills and analytical understanding
  • Master student in Computer Science, Robotics, Electrical Engineering or similar
  • Knowledge in (self-)supervised learning, transformer-based architectures, and foundation models
  • Knowledge of PyTorch, software development, Python, and C++
  • Structured work, commitment, and flexibility
  • Strong communication skills and analytical understanding

Education

Currently in higher education

Tasks

  • Assess open-source neural networks for automated driving
  • Leverage pretrained foundational models for network representation
  • Optimize networks for single-stage training and closed-loop performance
  • Adapt end-to-end models for predictive world model compatibility
  • Conduct experiments on public and internal datasets
  • Collaborate with machine learning experts and PhD students
  • Contribute to scientific research and publications

Tools & Technologies

PyTorchPythonC++

Languages

EnglishBusiness Fluent

Benefits

Other Benefits

  • Application assistance for disability
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