Master's thesis: Application of deep learning methods to 3D LiDAR environment data

Winter Semester 2025/26 – Fixed term for 6 months

YOUR TASKS:

• Develop intelligent algorithms for demanding outdoor applications based on 3D LiDAR data
• Explore state-of-the-art deep learning methods for 2D/3D environment perception (segmentation, object detection and classification)
• Train deep learning models and evaluate various algorithms in terms of accuracy and efficiency
• Work with cutting-edge 3D LiDAR sensors and gain hands-on technical experience
• Assess the applicability of deep learning methods on modern AI accelerators such as NVIDIA Jetson and Hailo
• Collaborate closely with engineers to develop innovative solutions
• Document your results in a structured and traceable manner

YOUR PROFILE:

• You are currently pursuing a master’s degree in computer science, physics, electrical engineering, mathematics or a related field
• You enjoy diving into new and challenging topics and developing novel solutions
• You have solid programming skills, ideally in C++ or Python
• You have initial experience with deep learning and frameworks such as TensorFlow or PyTorch
• You work in a systematic and structured manner
• Creativity in problem-solving and a passion for innovation round off your profile

YOUR APPLICATION:

• We are looking forward to your online application
• Sarah Disch
• Job-ID 37053 
• 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, Thesis, Masterarbeit