Job Description Complexity and scale of automotive systems are increasing, particularly in the area of automated driving and advanced driving assistance systems. The increased complexity of such safety-critical systems demands for advanced testing and verification methods to ensure safety under an abundance of operating conditions and traffic scenarios that may be encountered. Recently, generative AI has shown promising results for content generation, such as for text, image, or video generation. In our R&D work, we would like to explore the possibilities of using generative AI to create critical traffic scenarios learned from traffic data. We are seeking for a talented and driven Working Student (m/f/d) to join the Systems Engineering R&D team and support the development of testing methods by using recent results from generative AI for traffic scenario and video generation. In your role, you gain hands-on experience on the training and validation of generative AI models, and contribute to our R&D testing platform for automated driving. The work is part of the public funded project nxtaim.de. Responsibilities: Development of data pipeline to condition the traffic video generator on critical trajectories Conversion of trajectory and map data into dedicated format Integration of the pipeline into our existing traffic generation workflow Evaluate the traffic video generator to extract critical traffic scenarios