Intern / Thesis - Learning-based Radar-Camera Fusion for Simultaneous Localization & Mapping (m/f/d) Intern / Thesis - Learning-based Radar-Camera Fusion for Simultaneous Localization & Mapping (m/f/d) Intern / Thesis - Learning-based Radar-Camera Fusion for Simultaneous Localization & Mapping (m/f/d)

YOUR TEAM

To support our multimodal 3D sensing team, we are currently looking for an intern.  In your role, you get first-hand experience in radar-camera fusion and robust simultaneous localization and mapping (SLAM) for autonomous driving. You will be an integral part of the team working on cross-modal alignment, robust radar-camera odometry, and consistent map generation from radar and vision data.  Our team focuses on advancing multimodal algorithms that combine complementary sensing characteristics to enable reliable localization and mapping in complex driving environments under all weather and lighting conditions. This internship offers an opportunity to work on next-generation multimodal sensor fusion for autonomous driving, combining cutting-edge research with real-world automotive sensor data. 

WHAT YOU WILL DO

• Review literature of the current state-of-the-art algorithms and data sets 
• Implementing and benchmarking deep learning or geometric SLAM methods for baseline comparison 
• Developing and evaluating fusion pipelines for radar and camera data 
• Test and validate the results on real world automotive data 

WHO YOU ARE

• Excellent academic performance  

• Enrolled student in Computer Science, Robotics, Electrical Engineering, Mathematics or equivalent 

• Know-how of relevant sensors for autonomous driving and measurement technology 

• Programming knowledge and experience in Python or C++ 

• Confident in English in both oral and written form 

• High level of commitment, initiative, and teamwork. 

NICE TO KNOW

• Remote work options within Germany 

• Internship/Thesis: 

• Duration: 3 - 6 months 

• 35 h/week 

• Salary: 12,82€/hour