PhD Student Statistical Uncertainty Safety Argumentation Autonomous Driving (f/m/d) - #944590

Work environment

You are working in an international team on one of the most exciting and challenging topics in the automotive industry: developing autonomous driving for series production for ride-pooling customers! Together with colleagues from technical (commercial vehicle) development and a development partner, you are developing the ID. Buzz AD (Autonomous Driving) and next-generation autonomous vehicles. For the approval of autonomous vehicles, a holistic safety argumentation is required for the first time. This argumentation combines well-known safety domains such as functional safety, operational safety, and cybersecurity with process-related and organizational requirements to achieve the highest possible level of safety for autonomous vehicles. Your task is to create the safety argumentation for the AD function in a timely and complete manner. You will work as part of a team of AD function experts and experts from the different safety domains.

Possible Tasks within this Role

• Contributing to the safety assurance case for Level 4 autonomous driving
• Supporting the qualitative safety argumentation through quantification
• Researching the expression of uncertainty and confidence within the safety argumentation
• Investigating the use of safety performance indicators within the safety argumentation
• Linking uncertainty, confidence, and safety performance indicators into a coherent quantification framework
  
  

The final doctoral topic is defined together with the professor. The prerequisite for the cooperation is the confirmation of supervision as well as a confirmed delimitation of topics by the professor of a university or research institution entitled to confer a doctorate.

Qualification Requirements

• Good to very good university degree qualifying for doctoral studies in Computer Science, Physics, Electrical Engineering, Mechanical Engineering, Mathematics or a related field
• Knowledge of safety engineering (functional safety, SOTIF, etc.)
• Solid knowledge of an object-oriented programming language, e.g. Java
• English and German language level B2
• Strong analytical skills, quick comprehension, and willingness to familiarize oneself with new topics
• High level of independence and initiative, a goal-oriented work style, strong team spirit, and excellent customer orientation
  
  

Keywords

uncertainty representation, Dempster-Shafer theory, theory of evidence, subjective logic, Bayesian network, uncertainty propagation, safety case