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? This might be the right position for you as a research assistant and PhD candidate in generative AI for traffic digital twins.
Your responsibilities
- 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
Table of Content
Summary
- Application DeadlineOctober 31, 2025
- Study LevelPhD
- SponsorTechnical University of Munich (TUM)
- School to studyTechnical University of Munich (TUM)
- Eligible CountryAll Countries
Subscribe for Scholarship Alert!
Benefits
- 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
Requirements
- 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
Application Deadline
October 31, 2025How To Apply
- 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 [email protected] and [email protected] 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.
Contact: [email protected], [email protected]
For more information, kindly visit TUM scholarship webpage.
