PhD Student Agentic AI Process Design Automotive Production (f/m/d)

Work environment

As a PhD candidate in Corporate Industrial Engineering at the Volkswagen Group, you will work on a highly innovative research topic at the intersection of Generative AI, Agentic AI, process design, industrial engineering, and automotive production planning. The position is embedded in the planned IPCEI-AI European funding project, contributing to the development of next-generation AI capabilities for industrial process planning. The objective is to develop AI-based methods and prototypes that support process planners in the automated generation, evaluation, and continuous improvement of manufacturing process designs. Your work will focus on transforming product, engineering, and planning information into detailed, feasible, and explainable process steps for automotive assembly. The research will build on product-planning outputs and will be closely coordinated with an already established PhD project focusing on AI-supported product planning. In addition to conducting scientific research, you will take on a key role as Product Owner for prototype development. This includes translating research requirements into prototype features, coordinating implementation priorities, and ensuring close alignment between AI development, industrial users, IT, and project stakeholders. The position builds on an existing research direction in Generative AI for autonomous process planning systems, which already emphasized AI model development, mathematical modeling, algorithm design, pilot projects, and collaboration with industrial engineering experts.

Possible tasks within this role

• Developing AI-based methods for process design that generate feasible assembly process steps from product, engineering, and planning data
• Designing and implementing agentic AI workflows using DeepAgents, LangChain, Python, tool-calling, memory, and retrieval mechanisms
• Acting as Product Owner for prototype development, translating research needs into features, user stories, priorities, and validation criteria
• Collaborating closely with the AI product-planning PhD project to integrate product-planning outputs into process-design logic
• Evaluating AI-generated process designs against expert-created reference plans using quality, completeness, sequence, and explainability metrics

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, with a specialization in Artificial Intelligence
• Deep expertise in Generative AI, Agentic AI, Large Language Models and LangChain DeepAgents
• Very strong Python development skills, including AI prototypes, data pipelines, APIs, evaluation scripts, and software integration
• Solid knowledge of RAG architectures, embeddings, vector databases, prompt engineering, and AI system design
• Strong ability to work at the interface of research, prototype development, industrial users, IT teams, and funded project environments

The following documents must be submitted with the application

• Curriculum Vitae
• Current transcript of records / Master’s or Diplom degree certificate

Keywords

Autonomous Manufacturing Planning, Multi-Agent Systems, Knowledge-Based Planning, Digital Process Planning, Cognitive Manufacturing, AI Orchestration, Production Logic Generation, Intelligent Workflow Planning, Semantic Knowledge Graphs, Manufacturing Process Intelligence