PhD Student AI-Aided Product Development - Process Intelligence and Knowledge Management (m/f/d)

Your home area “Engineering Strategy” is responsible for the strategic development of our research and development: from the development strategy to the process and method landscape to the question of how artificial intelligence creates real added value in commercial vehicle development. AI tools are currently developing faster than development organisations can integrate them in a meaningful way. The limiting factor is rarely the model, but the quality, structure and accessibility of the underlying process, knowledge and data base. Right here is your doctorate: You develop a methodological approach that systematically identify, evaluate and introduce AI tools for development. The research work develops an expandable AI-Aided Process Tool based on a machine- and human-readable metamodel, as well as a method for systematically combining process requirements and AI capabilities. The aim is to continuously optimize our process landscape through the targeted use of AI. You validate your results in real applications - from AI-based, context-specific knowledge provision for employees to data-based identification of optimization potentials. You work closely with process managers, IT and engineering disciplines to translate practical requirements into scientific questions and to bring research results into industrial application. This research work is a cooperation project with the University of Stuttgart, where your doctoral degree is also taking place. Your place of service is Stuttgart; for cooperation with the development areas and for process recordings on site, you bring travel readiness to our development location Munich. The employment is carried out as a scientific assistant with the possibility of doctoral studies; the project duration is 36 months. Your tasks Analysis of existing development processes and their documentation and identification of systematic gaps structuring, harmonising and transferring heterogeneous process and knowledge documentation into the developed metamodel and building a machine-readable knowledge base Development of a metamodel and a standardized survey scheme for machine and human-readable process and knowledge documentation Scaled collection and construction of a structured process knowledge base including effort measurement Development of an ability-taxonomy of AI landscape and a reproducible method for selecting and evaluating AI tools Conception, implementation and controlled evaluation of demonstrators (AI-based knowledge access, process optimization) Documentation, evaluation and results as well as derivation of a benefit-object assessment Publication of results in international journals and corresponding conferences

Your qualifications Good Master's degree entitled to Doctorate in Mechanical Engineering, Data Science, Industrial Engineering, Computer Science, Business Informatics or Related Study Courses Good knowledge of German and English Interest in scientific work with high application reference Experience in product development, process modelling (e.g. BPMN) or knowledge management Knowledge in the field of Artificial Intelligence, in particular Large Language Models, RAG or Knowledge-Graph Approaches Experience with empirical methods (interviews, observation, qualitative content analysis, user studies) of advantage Programming skills in Python Impressed communication strength and joy in working with different disciplines Self-employed, structured working and readiness to travel to Munich