This challenge awaits you:
• As part of our development and research activities in the field of automated driving (AD/ADAS), we are looking for motivated students who want to contribute to innovative and future-oriented topics in the context of virtual validation.
• The focus is explicitly on offline-based methods for data analysis as well as the development and improvement of simulation and perception models for virtual validation. There is no real-time ECU or in-vehicle implementation work involved.
• We focus on cutting-edge AI methods for vehicle perception as well as high-fidelity physical sensor models for virtual development and testing environments. You will work at the intersection of artificial intelligence, simulation, and data-driven modeling.
• Depending on your interests, we will jointly select a suitable topic in the interview and flexibly define the scope for a master thesis.
• You will also be part of an international team, collaborating closely with colleagues across multiple global locations and contributing to cross-site development and research activities.
Your Tasks:
Master Thesis in AI-based AD/ADAS Virtual Validation
This challenge awaits you: • As part of our development and research activities in the field of automated driving (AD/ADAS), we are looking for motivated students who want to contribute to innovative and future-oriented topics in the context of virtual validation. • The focus is explicitly on offline-based methods for data analysis as well as the development and improvement of simulation and perception models for virtual validation. There is no real-time ECU or in-vehicle implementation work involved. • We focus on cutting-edge AI methods for vehicle perception as well as high-fidelity physical sensor models for virtual development and testing environments. You will work at the intersection of artificial intelligence, simulation, and data-driven modeling. • Depending on your interests, we will jointly select a suitable topic in the interview and flexibly define the scope for a master thesis, mini thesis, internship, or working student position. • You will also be part of an international team, collaborating closely with colleagues across multiple global locations and contributing to cross-site development and research activities.
Your Responsibilities:
Topic Area 1:
Vision-Based Perception & Scene Understanding (Virtual Validation)
• Further development of innovative approaches in visual perception for automated driving in the context of offline analysis and virtual validation
• Research and implementation of methods for scene understanding, reasoning, and contextual interpretation of traffic situations
• Development and analysis of hybrid AI architectures (classical computer vision combined with vision and large language models)
• Investigation of robust scenario recognition methods in complex on- and off-highway simulation environments • Validation and evaluation of model behavior based on simulation or recorded measurement data
Topic Area 2:
Physical Sensor Modeling & Simulation
• Further development of physically based sensor models for camera, radar, and lidar systems within virtual development environments
• Application and extension of simulation frameworks such as dSPACE ASM, CarMaker, Ansys, and MATLAB/Simulink
• Improvement of realism and accuracy of synthetic sensor data for ADAS/AD validation processes
• Integration and comparison of different sensor models in the context of data-driven offline analysis
• Investigation of innovative approaches for improving efficiency and scalability of simulation and validation pipelines
Necessary Skills:
• Currently enrolled in a degree program in Computer Science, Robotics, Mechatronics, Electrical Engineering, or a related field
• Advanced knowledge in at least one of the following areas:
• Computer Vision / Perception • Artificial Intelligence / Deep Learning / LLMs / VLMs • Simulation / Physical Modeling
• Strong programming skills in Python (C++ or MATLAB is a plus)
• Experience with modern AI frameworks (e.g., PyTorch, OpenCV, transformer-based models)
• Ideally experience with cloud environments or distributed systems
• Interest in data-driven, scientific, and model-based analysis approaches
• Independent, analytical, and structured working styl
Desired Skills:
You won’t just be working anywhere as a student at IAV. You’ll be right in the middle of it all. Real projects. Exciting future tasks. Completely integrated and side-by-side with IAV experts. Lots of responsibility and at the same time lots of freedom, combining university and work. The result is the best prospects for your professional development. And attractive compensation in accordance with our company wage agreements.
Diversity and equal opportunity are important to us. What matters to us is the individual, with his or her character and strengths.