Call for Master’s Thesis Candidates

Object List Generation and Extraction for V2X Communication

Chair of Robotics, Artificial Intelligence and Real-time Systems
TUM School of Computation, Information and Technology

Project Description

You will design and implement a modular, real-time processing chain that fuses camera, LiDAR and radar data to:

• Detect and classify objects using state-of-the-art algorithms (e.g. YOLO, PointNet)
• Track object positions and estimate their speeds (Kalman/particle filters)
• Predict future trajectories with probabilistic modeling
• Optimize data compression and error-correction strategies for efficient V2X transmission
• Validate the overall system in both simulation and real-world experiments

Your Tasks

• Develop the multi-sensor fusion pipeline in Python and C++
• Integrate and fine-tune deep learning detection models
• Implement tracking and trajectory-prediction modules
• Design data-compression schemes and assess communication reliability
• Run benchmarks, analyze performance, and document your findings

Your Profile

• Enrolled in a Master’s program (Computer Science, Electrical Engineering, Robotics or related)
• Strong programming skills in Python and C++
• Experience with machine learning frameworks (TensorFlow, PyTorch)
• Familiarity with object detection (CNNs, Transformers), tracking algorithms and probabilistic methods
• Basic understanding of V2X protocols (DSRC, C-V2X) and real-time system constraints
• Good communication skills and ability to work both independently and in a team

We Offer

• Hands-on research experience with industry-relevant use cases
• Access to state-of-the-art sensor hardware and simulation platforms
• Close mentorship from leading AI and robotics experts
• Opportunity to co-author publications and present at conferences
• Flexible working hours and a collaborative lab environment

How to Apply

Please send the following documents as a single PDF to kuoyi.chao@tum.de with the subject line “Master’s Thesis Application – Object List Generation for V2X”:

1. Curriculum vitae
2. Transcript of records
3. A brief motivation letter (max. 1 page)

Review of applications begins immediately and continues until the position is filled. We look forward to your application!