Master Thesis Application of Generative AI to Automotive Safety Engineering(m/w/x)

## Job Description * The overall research goal is to investigate and demonstrate Generative AI's potential to enhance automotive safety engineering through a mixed-methods approach and a proof-of-concept. * During your assignment, you will use existing safety engineering workflows to identify Generative AI integration opportunities. * You will employ mixed-methods (quantitative and qualitative) to gather data on stakeholder perspectives and key performance indicators (KPIs). * Furthermore, you will identify needs, challenges and critical success factors for Generative AI adoption based on the collected data. * Last but not least, you will develop and implement a proof-of-concept demonstrating the practical application and value of Generative AI in a specific safety engineering activity in the automotive industry. ## Qualifications * **Education:** Master studies in the field of Computer Science, Software Engineering, Embedded Systems, Artificial Intelligence or comparable * **Experience and Knowledge****:** in Python; Anaconda; Generative AI (GenAI); Large Language Models (LLM); JSON; JavaScript; HTML; FastAPI; GitHub; Retrieval-Augmented Generation (RAG) and Transformer architectures * **Personality and Working Practice:** you are a trustworthy and enthusiastic person with a meticulous way of working * **Languages:**  very good in English, German is a plus ## Additional Information **Start:** according to prior agreement **Duration:** 6 months Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit. Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.