Winter Semester 2025/26 – Limited to 3-6 months, Start possible from 01.09.2025
YOUR TASKS:
* Develop algorithms for environmental perception to prevent collisions of mobile robots and machines.
* Research and apply state-of-the-art deep learning methods for 2D/3D environment perception (segmentation, object detection, and tracking).
* Train deep learning models and evaluate various algorithms.
* Design a multi-sensor system for 3D environmental perception, e.g., for obstacle detection in logistics applications or outdoor environments.
* Process and fuse high-resolution RGB and depth data from real or simulated stereo or RGB-D cameras.
* Integrate, optimize, and evaluate systems on state-of-the-art AI accelerator hardware such as NVIDIA Jetson and Hailo.
* Document your work results in detail.
YOUR PROFILE:
* You are currently pursuing a Master’s degree in Computer Science, Robotics, Mathematics, or a related field.
* You have strong programming skills, ideally in C++ or Python.
* You have a solid understanding of image processing and working with 2D and 3D data.
* You have expertise in deep learning and machine learning, with experience in frameworks such as TensorFlow or PyTorch.
* Ideally, you have knowledge of applications involving mobile robots or autonomous driving, e.g., using ROS and/or NVIDIA Jetson.
* Your systematic and structured thinking and approach set you apart.
* Creativity in problem-solving and enthusiasm for innovation complete your profile.
YOUR APPLICATION:
* We are looking forward to your online application
* Sarah Disch
* Job-ID 36765
* 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: Abschlussarbeit