Job Description:

The Cooperative Autonomous Systems Research Group at the AIFB Institute is at the forefront of research and innovation in connected and autonomous vehicles. Our mission is to leverage state-of-the-art technologies to enhance road safety and actively shape the future of intelligent mobility.

We are seeking a highly motivated Student Assistant (m/f/d) to support our ongoing research activities in the areas of computer vision, deep learning, and multi-sensor systems. The successful candidate will contribute to both practical and research-oriented tasks related to multi-modal sensor calibration, data processing, and algorithm development and evaluation. This position offers an excellent opportunity to gain hands-on experience in cutting-edge research projects and to collaborate closely with researchers in an international and interdisciplinary environment.

Your Tasks:

• Conduct a literature review on spatial-temporal calibration methods
• Evaluate and test existing calibration approaches using open-source datasets
• Process and analyze multi-modal sensor data (LiDAR, RGB, Thermal, etc.)
• Perform spatial-temporal calibration on in-house datasets
• Support the preparation and submission of results to international conferences

Your Profile: 

• Solid programming skills in Python, C++
• Solid knowledge of computer vision and/or deep learning • Experience with common libraries and frameworks (e.g., OpenCV, PyTorch, TensorFlow, ROS2) is a plus
• Familiarity with sensor systems (e.g., LiDAR, RGB, Thermal, GPS, IMU)
• Structured, independent, and reliable working style

What we offer:

• Flexible working hours
• Industry and research related activities
• Contribution to publications
• Working with the latest technologies
• Coffee and great colleagues