Description

Life is always about becoming… Becoming means going on a journey to be the best version of our future selves. While we discover new things, we will face challenges, master them and grow beyond our individual limits.

Apply for a job at Mercedes-Benz and find your individual role and workspace to unleash your talents to the fullest. Empowered by visionary colleagues who share the same pioneering spirit. Joining us means becoming part of a global team that aims to build the most desirable cars in the world. Together for excellence.

Job-ID: MER0003GY7

The Mercedes-Benz Group AG, one of the world’s most successful automotive companies, is a leading provider of premium and luxury cars and vans. In Corporate Research & Development (RD), we shape future automotive generations with innovative, high-quality products and efficient processes. We are committed to developing highly automated driving systems for highways and urban areas, leveraging state-of-the-art technologies across our teams in Germany, India, China, and the US. To maintain our technological leadership and ensure exceptional customer experiences, we seek talented and dedicated Ph.D. students to join our automated driving (AD) development team in Sindelfingen.

The focus of your Ph.D. will be on developing a runtime monitoring system for autonomous driving functions. This system aims to identify unknown operation points based on empirical data from functional tests, ensuring safe and reliable operation post-deployment. Your research will involve creating a theoretical framework and practical methodologies to enhance the safety and reliability of autonomous driving systems. The primary objective is to devise a method that dynamically monitors system operation, identifies unknown operation points, and triggers corrective actions to maintain safety, all while satisfying statistical guarantees.

You will work at the intersection of AD system development, system testing, and safety, under the supervision of experts in the field. During your research, you will utilize the latest machine learning techniques, such as out-of-distribution detection, conformal prediction, and statistical machine learning. You will have access to extensive data from system development and testing, including real and simulated recordings. Your findings will not only enhance the safety of high-level automated driving but also contribute significantly to the research community. We strongly encourage and support the publication of your work.

Responsibilities…

  • Assess the current state-of-the-art in runtime monitoring of safety-critical robotics applications including but not limited to automated driving
  • Advance your knowledge in related fields like statistical machine learning, machine learning with guarantees, conformal prediction, and out-of-distribution detection
  • Develop statistical models and algorithms to monitor system operation points
  • Collect and analyze data from diverse test drives, including both real-world and simulated recordings
  • Validate the efficacy of the developed models through available data, simulation and additional test drives
  • Integrate the monitoring system into test vehicles
  • Organize the recruiting and supervision of students to contribute to your research
  • Document research findings and publish in scientific articles

Would you like to write your dissertation in cooperation with Mercedes-Benz Group AG? We offer you an international network of experts, research materials, insights into our work and a personal mentor who will be available to you as a contact person alongside your doctoral supervisor at your university. The recruitment requirement is that a university lecturer supervises the doctoral project. The doctoral student is responsible for selecting an appropriate supervisor.

What you bring to the table:

  • Excellent master’s degree in mathematics, statistics, computer science, machine learning, robotics, or related areas
  • Excellent programming skills in Python or C++
  • Strong knowledge and in-depth understanding of machine learning techniques including deep learning and the corresponding software frameworks (e.g., pytorch, tensorflow)
  • Experience with public cloud infrastructure (GCP, AWS or Azure)
  • Experience with Linux and development on Linux Systems
  • Fluent English skills

Preferred Qualifications…

  • Knowledge in robotics, testing or safety
  • Basic knowledge of ADAS/AD architectures
  • Excellent communication skills and desire to work as part of a global team in a multi-cultural environment
  • Publication at a machine learning or robotics conference is a plus
  • High intrinsic motivation to perform cutting-edge research
  • High self-organization
  • Fluent proficiency in spoken and written German (optional)

Additional information:

Would you like to write your doctoral dissertation in cooperation with Mercedes-Benz Group AG? We offer you an international network of experts, research materials, insights into our work and a personal mentor who will serve as your contact partner in addition to your doctoral advisor at your university.

Please apply exclusively online and mark your application documents as “relevant for this application” in the online form. Please find the criteria of employment “here”. Citizens of countries outside the European Trade Union please send, if applicable, your residence / work permit.

We particularly welcome online applications from candidates with disabilities or similar impairments in direct response to this job advertisement. If you have any questions, you can contact the local disability officer once you have submitted your application form, who will gladly assist you in the onward application process: sbv-sindelfingen@mercedes-benz.com

Please understand that we do not accept paper applications and that there is no right to get your documents returned.

If you have any questions regarding the application process, please contact HR Services by e-mail at myhrservice@mercedes-benz.com or by phone: 0711/17-99000 (Monday to Friday between 10 a.m. to 12 a.m. and 1 p.m. to 3 p.m.).

If you have any questions concerning the position, please contact Mr. Julian Wiederer at the following E-Mail adress: julian.wiederer@mercedes-benz.com

  • Meal-Discounts
  • Mobile Phone possible
  • Discounts for employees possible
  • Annual profit share possible
  • Events for employees
  • Coaching
  • Flexitime possible
  • Hybrid Work possible
  • Health Benefits
  • Company Retirement
  • Mobility offers