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infrastructure, vehicles, and humans. Your responsibilities High-quality research on generative AI methods(LLMs, VLMs, diffusion models) with a strong connection to traffic simulation, autonomous driving, and
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supporting multiple sensors (LiDAR, radar, camera) for dynamic environments like ports, airports, and logistics hubs. Optimize algorithms for real-time operation on edge devices with limited computational
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(clinic & AI) Modern work environment with state-of-the-art facilities and infrastructure Access to unique clinical datasets and high-performance computing Flexible working hours (19.25–38.5 h/week), 30
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entrepreneurship education Data-driven optimization: Establish a systematic assessment and mapping of TUM's entrepreneurship education components to talent journeys Program development: Contribute to strategic
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labeled data and that the learned intelligent agents can perform better than humans. Instead of verifying the correctness of neural networks, we build a safety net that only forwards safe actions
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permanent funding as part of the German and Bavarian government's AI strategy. Our vision is to strengthen regional, national, and international competence in AI and to make the corresponding potential
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for 3 - 6 years, with the option to enter the habilitation program in the format of 3 + 3 years. The salary will be determined according to the German collective wage agreement in public service (TV-L 13
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for two years, with the possibility of extension, depending on performance and project needs. Qualifications • For Doctoral Candidates: Master’s degree in Computer Science or Mathematics. • For Postdoctoral
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systems. Design and implement algorithms that enable shared control between human operators and autonomous systems to improve teleoperation performance. Maintain active communication and collaboration with
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, Human-Computer Interaction, and their responsible applications. Ideal candidates will have: An M.Sc. degree (or equivalent) in Computer Science, Game Engineering, Mathematics, Statistics, or related