PhD Student Agentic AI Process Design Automotive Production (f / m/d) | PhD students
Wolfsburg, Germany
Key offer highlights
Backend: Java / .NET / Node / Python
Employment: contract
Looking for experts - senior/expert
Full-time
Description
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. 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 What we offer The gross monthly salary for this position, based on a 35-hour workweek and scaled according to the respective year of employment, is €3,030 (1st year), €3,194 (2nd year), and €3,497 (3rd year). In addition, there is a monthly allowance of €167 as well as a 49% share of the variable bonus. Contact person for this posting: Fabian Wenzel 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
Company
Volkswagen AG
Contract
Fixed-term
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.
Department
IT and Digitalization
Shift
Full-time
Experience
PhD students
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
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 following documents must be submitted with the application
Curriculum Vitae
Current transcript of records / Master’s or Diplom degree certificate