Description
The Technical University of Munich (TUM) Autonomous Vehicle Systems Lab is officially accepting applications for five open research roles. This initiative is designed for highly motivated researchers and scholars who want to advance the field of robotics, artificial intelligence, and self-driving technologies. Selected candidates will have the chance to join a collaborative and innovative team pushing the operational limits of intelligent systems. This program offers an elite environment to develop advanced research skills, tackle complex engineering problems, and build an impactful professional network within academia and the automotive industry.
Responsibilities & Available Positions
The lab is currently recruiting for five distinct academic and research tracks. Candidates will be expected to conduct independent research, publish findings, and contribute to cutting-edge projects. The available openings include:
- Postdoctoral Researcher – Mobile Robotics: Focuses on advanced localization, mapping, and navigation strategies for mobile robotic systems.
- PhD Position in Mobile Manipulation for Humanoids: Centers on integrating robotic arms with mobile bases to improve real-world tasks for humanoid robots.
- PhD Position in End-to-End Software for Autonomous Driving: Involves designing and testing fully integrated neural network pipelines for self-driving vehicles.
- PhD Position in Intelligent Scenario Generation for Autonomous Vehicles: Focuses on building smart, simulation-based testing environments to evaluate safety critical driving scenarios.
- PhD Position in Artificial Intelligence in Motorsports: Dedicated to developing high-speed AI racing algorithms, predictive modeling, and vehicle optimization tools.
Funding Coverage & Benefits
Joining the TUM Autonomous Vehicle Systems Lab provides a comprehensive platform for high-impact scientific research and career development. While specific salary scales depend on standard public sector university contracts, the positions offer:
- Top-Tier Research Environment: Access to state-of-the-art computational frameworks, simulation tools, and real-world autonomous vehicle testing platforms.
- Professional Networking: Direct collaboration with industry partners, leading engineers, and global research consortia in autonomous systems.
- Structured Mentorship: Dedicated guidance from senior professors and experienced research fellows to prepare candidates for careers in industry-led innovation and academia.
Qualification & Candidate Profile
The lab seeks talented individuals with strong mathematical, programming, and technical backgrounds. The general candidate criteria include:
- Target Audience: The openings are structured for one postdoctoral scholar and four doctoral (PhD) researchers.
- Academic Background: Applicants should hold a relevant master's or doctoral degree in Computer Science, Engineering, Robotics, Data Science, or a closely related quantitative field.
- Technical Skills: Strong familiarity with AI frameworks, autonomous software, or robotic systems is highly valued depending on the specific track.
- Core Attributes: A proactive learning attitude, strong problem-solving skills, and the capacity to work within a multidisciplinary team.
Application Procedure & Key Dates
The selection process follows a strict institutional timeline. Interested candidates must follow the steps below:
- Review Position Details: Visit the official lab portal to read the specific technical requirements for your chosen track.
- Submit Your Application: Navigate to the respective position page on the official website and upload your application materials through the designated portal.
- Application Deadline: All applications must be submitted by 17 July 2026.
- Interview Window: Shortlisted candidates will participate in formal evaluations held between 1 August and 18 August 2026.
- Official Start Date: Successful applicants will officially begin their positions on 1 October 2026.
- To review full descriptions and submit your materials, please refer to the official application platform.
