PhD Position in Generative AI for Intelligent Traffic Systems

27.10.2025, Wissenschaftliches Personal

Are you passionate about generative AI and digital twins for intelligent mobility systems? Do you see potential in using large language models, vision-language models, or diffusion models to simulate and design complex urban traffic environments? Do you want to shape the next generation of data-driven mobility intelligence with your creative ideas and research? We might just have the right position for you as a research assistant and PhD candidate in generative AI for traffic digital twins.

The Chair of Robotics, Artificial Intelligence and Real-Time Systems operates a state-of-the-art research infrastructure for intelligent transportation systems in the adjacent urban areas of Garching-Hochbrück near Munich. Building on this foundation, we extend toward generative and multimodal AI methods that connect simulation, perception, and control within large-scale digital twins of urban traffic systems in Munich. The focus lies on advancing semantic interpretation of complex traffic scenes, AI-based control of automated vehicle movements, and adaptive traffic management strategies that enable data-driven understanding and real-time interaction between infrastructure, vehicles, and humans.

• High-quality research on generative AI methods(LLMs, VLMs, diffusion models) with a strong connection to traffic simulation, autonomous driving, and digital twin systems
• Participation in research projects, execution of project deliverables, and generation of reports
• Maintain and develop the live testbed infrastructure for real-world experimentation and demonstration
• Regular publication of results in high-impact and peer-reviewed journals and conferences
• Assistance and active participation in the drafting of research proposals and participation in periodic academic assignments at the chair

• Completed master’s degree in computer science, transportation, or related engineering fields
• Solid background in generative AI, machine learning, and autonomous systems
• Fluent English (spoken and written); German proficiency is a strong plus
• Ability to work independently, willingness to learn and acquire new competence
• Strong programming skills (Python, C++) and experience with machine learning frameworks
• Exposure to simulation frameworks (SUMO, CARLA) is a strong advantage

• A full-time position within a leading research group in autonomous systems and artificial intelligence
• Participation in high-impact and visionary research projects
• Collaboration with leading research institutions in the field of intelligent mobility
• An opportunity to make a visible impact, earn a doctorate degree, and much more

The employment will be as per TV-L E13 on a fixed-term contractual basis. The Chair of Robotics, AI and Real-Time Systems at Technical University of Munich (TUM) strives to increase the proportion of women employees and therefore strongly encourages relevantly qualified women to apply. Severely disabled persons are given preference upon equal suitability and qualification.

Please send your application consisting of a motivation letter, curriculum vitae, copies of your degrees and transcripts, employment certificates and any other relevant documents — all combined into one PDF file not exceeding 10 MB in size — to marie-luise.neitz@tum.de and xingcheng.zhou@tum.de latest by October 31, 2025. Please use the text Application RA_ITS_202510_A in the subject field of the email and provide your expected earliest starting date. Early applications are encouraged.

Personal information submitted as part of your application will be processed in accordance with Art. 13 of GDPR. Please check the relevant TUM data protection information for details.

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: marie-luise.neitz@tum.de, xingcheng.zhou@tum.de

https://www.ce.cit.tum.de/fileadmin/w00cgn/air/Job_Offers/Stellenausschreibung_RA_202510.pdf