PhD student for PhD thesis on validation strategies for E2E DNNs in automated driving

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Number: MER0003XTO Within the development of ADAS/AD functions, AI-based end-to-end (E2E) architectures are becoming increasingly important. E2E architectures have the potential to reduce the complexity of traditional modular architectures and enable a more direct mapping of sensor data to drive commands using deep neural networks (DNN). This doctorate deals with the complex challenges and innovative solutions in securing E2E-DNNs. Your tasks include: Stand-of-Technology Analysis Considering AI Security Research Landscape and Established Safety Standards in Automotive Engineering (ISO 26262, ISO 21448, ISO/PAS 8800) Analysis of specific challenges in securing E2E-DNNs compared to traditional modular DNN architectures related to requirements, V&V, monitoring and safety argumentation Identification of suitable starting points in the E2E safety argumentation and development of innovative solutions Regular presentation of your results in the project Documentation and publication of your results in a dissertation The activity can start from April2026. Adjustment requirement is the support of the doctoral project by a university lecturer. The selection of a corresponding person is the responsibility of the doctoral student.

Complete degree or master studies in the field of engineering, mathematics, computer science or comparable Secure knowledge of German and English in word and writing Analytical thinking and strategic working Experience in statistics, artificial intelligence and machine learning desirable Programming experience for example in Python, Matlab or C Commitment and team skills

Additional information: Doctorate in the Mercedes-Benz Group! Benefit from our know-how, an international expertise network, research materials, work insights and personal support by mentors – in addition to your university. Further information can be found here. We look forward to your online application with CV, Letters and Certificates. Please do not forget to mark your documents as ''relevant for this application' in the online form and note the maximum file size of 5 MB. Disabled and equalized applicants are welcome! The severely disabled representative (sbv-Sindelfingen@mercedes-benz.com) is happy to support you in the application process. HR Services will be happy to help you with questions about the application process. You can reach us by email via myhrservice@mercedes-benz.com or by phone at 0711/17-99000 (Mo-Fr 10-12am & 13-15am).

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