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24Open Positions

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INTERNSHIP/THESIS: WORLD MODELS FOR AUTOMOTIVE RADAR SIGNAL SIMULATION(F/M/D)

FORVIA HELLA
Found 1 month ago
Location
Lippstadt, Germany
Duration (Months)
3 Months
Time
Not disclosed
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • Python
  • PyTorch
  • generative models
  • diffusion models
  • flow matching
  • VAEs
  • state-space models
  • world models
  • 3D scene representations
  • NeRF
  • implicit fields
  • 3DGS
  • deep learning
  • generative AI
  • autonomous driving

Soft Skills

  • Scientific writing

Job Description

Are you passionate about deep learning, generative AI, and autonomous driving and would you like to become part of a forward-looking technology field? As part of an internship or thesis project with a focus on Generative AI (GenAI) at the E-LAB (www.the-e-lab.de), you will have the opportunity to actively contribute to the development of intelligent sensor systems for automated vehicles. Literature research: You analyze current approaches for the synthetic generation of radar signals. Model development: Contribute to the development of generative machine learning models, for example diffusion models, for radar data generation. Data comparison and evaluation: Compare and evaluate generated data against real radar measurements with regard to physical plausibility and statistical properties. Scientific writing: Your tasks include scientific writing for the preparation of a comprehensive final report.

Requirements

  • You are enrolled at a university during your time at HELLA and have not yet started or completed your final mandatory study requirement.
  • You are currently pursuing a Master’s degree in Electrical Engineering, Computer Science, or a comparable field of study.
  • You have strong programming skills in Python and practical experience with PyTorch.
  • You have experience in one or more of the following areas: generative models such as diffusion models, flow matching, or VAEs, state-space models or world models, as well as 3D scene representations such as NeRF, implicit fields, or 3DGS.
  • You have very good German or English language skills (at least C1 level).

Related Field

  • Software Engineering

Related Subfield

  • AI/ML/GenAI Engineering

Languages

  • German
  • English
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