Summer Semester 2025 - fixed-term for 3-6 months


YOUR TASKS:

  • You design a system for 3D environment detection to avoid collisions of mobile robots, for example, in logistics applications.
  • You conduct literature research and explore current deep learning methods for 2D/3D environment detection (segmentation, object recognition, and tracking) and sensor fusion.
  • You process and fuse high-resolution RGB and depth data from real and simulated Time-of-Flight and RGB-D cameras.
  • You develop algorithms for environment detection with the goal of avoiding collisions of mobile robots.
  • Training deep learning models and evaluating various algorithms are part of your tasks.
  • You integrate, optimize, and evaluate the systems on the current NVIDIA Jetson hardware.
  • You document your work results in detail.

YOUR PROFILE:

  • You are pursuing a master’s degree in computer science, robotics, mathematics, or a comparable field.
  • You have solid knowledge of programming languages, ideally in C++ or Python.
  • You possess a comprehensive understanding of image processing and handling 2D and 3D data.
  • You have expertise in deep learning and machine learning, with initial experience in frameworks such as TensorFlow or PyTorch.
  • Ideally, you have knowledge of robotics and robot applications, e.g., with ROS and NVIDIA Jetson.
  • Your systematic and structured thinking and approach set you apart.
  • Creativity in problem-solving and a passion for innovation complete your profile.

YOUR APPLICATION:

  • We are looking forward to your online application
  • Sarah Disch
  • Job-ID 36414 
  • All applications will be treated confidentially

*At SICK, we see people, not gender. 

We put great emphasis on diversity, reject discrimination and do not think in categories such as gender, ethnicity, religion, disability, age or sexual identity.

Stichworte: Intern, Internship, Abschlussarbeit 

Location

Waldkirch (bei Freiburg), DE, 79183

Job Overview
Job Posted:
3 months ago
Job Expires:
Job Type
Full Time

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