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9Open Positions

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INTERNSHIP/MASTER'S THESIS: RADAR-BASED PERCEPTION FOR AUTONOMOUS DRIVING WITH DEEP LEARNING (F/M/D)

FORVIA HELLA
Found 1 month ago
Location
Lippstadt, Germany
Duration (Months)
6 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

  • deep learning
  • autonomous driving
  • RADAR
  • LiDAR
  • cameras
  • Python
  • PyTorch
  • computer vision
  • multi-sensor fusion
  • diffusion models
  • scene flow

Soft Skills

  • eager to contribute
  • actively contribute
  • help shape

Job Description

Are you passionate about deep learning and autonomous driving and eager to contribute to a revolutionary technology? As an intern or master's thesis student with a focus on perception in the E-LAB (www.the-e-lab.de), you will have the opportunity to actively contribute to the development of intelligent vehicles. Working closely with our team, you will support innovative neural network approaches for environmental perception in autonomous driving and help shape the mobility of tomorrow. The position is available immediately and has a minimum duration of six months. Literature Research: You conduct comprehensive literature research on perception methods using RADAR, LiDAR and cameras. Framework Implementation: You implement and compare different open-source frameworks for the perception of automated driving. Neural Networks: You train neural networks and analyze the results. Documentation: You document your work throughout the implementation phase and present your results after the internship or master's thesis.

Requirements

  • Enrolled Student: You are enrolled at a university throughout your time at HELLA and have not yet completed your final examination.
  • You are studying computer science, electrical engineering, computer science or a comparable master's degree program with a focus on machine learning and deep learning.
  • You have solid programming skills in Python and are familiar with PyTorch, ideally demonstrated through practical project experience, for example via GitHub.
  • You have strong knowledge of deep learning and computer vision. Ideally, you also have experience in one or more of the following areas: multi-sensor fusion, diffusion models or scene flow.

Related Field

  • AI & Machine Learning

Related Subfield

  • Deep Learning

Languages

  • German
  • English

Nice to Haves

  • multi-sensor fusion
  • diffusion models
  • scene flow
▶Apply Now

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