PhD student Machine Learning – Safety Monitoring in Autonomous Driving

Job title: PhD student Machine Learning – Safety Monitoring in Autonomous Driving

Company: Mercedes-Benz


Job 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: MER0003PK0
AufgabenThe 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.Your Ph.D. will focus on developing a safety monitoring system for autonomous vehicles. This system aims to ensure safe operation by identifying unknown operational points using empirical data from functional tests. It leverages vehicle sensor signals and planned behavior as inputs to detect system failures. Your research will involve practical methodologies and the creation of a theoretical framework.The primary objective is to devise a method that dynamically monitors system operation, detects failures, and triggers corrective actions, maintaining safety 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 including generative methods such as multi-modal large language models (MLLMs), multi-modal representation learning, out-of-distribution detection and conformal prediction.You will have access to extensive data from system development and testing, including real and simulated on-vehicle 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 representation learning, generative models, multi-modal LLMs, statistical machine learning, machine learning with guarantees, conformal prediction, and out-of-distribution detection
• Develop probabilistic models and algorithms to monitor the system’s 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

The Promotion can begin from October 2025.The requirement for hiring is the supervision of the PhD project by a university lecturer. The PhD student is responsible for choosing his/her/their own supervisor.
Profil

• 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 . 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: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 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 .
Wir bieten

• Meal-Discounts
• Mobile Phone for Employees Possible
• Discounts for Employees Possible
• Annual Profit Share Possible
• Events for Employees
• Coaching
• Flextime Possible
• Hybrid Work Possible
• Health Benefits
• Company Retirement
• Mobility Offers

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Expected salary:

Location: Sindelfingen, Baden-Württemberg

Job date: Wed, 16 Jul 2025 07:47:02 GMT

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