PhD Student Manufacturing Variations Control - Best‑Fit Assembly (f/m/d)

Work environment

The Assembly Planning Department within Volkswagen Brand Planning is responsible for the conceptual development and implementation of assembly systems for vehicle ramp-ups, as well as for the engineering of automated assembly processes across all global Volkswagen production sites. In close collaboration with manufacturing plants, Technical Development, Product Planning and experts from electrical and automation engineering, we design, evaluate, and validate forward-looking assembly concepts to enable the next generation of automotive production systems. In the context of increasing production complexity, the integration of real-time process data into upstream and downstream assembly stages is gaining substantial relevance. Particularly in exterior assembly, the control- and compensation-based management of manufacturing variations constitutes a critical lever for achieving long-term improvements in product quality and gap-dimension precision. Emerging automation technologies, interconnected process architectures, and advanced control strategies play a decisive role in this endeavor. The proposed research project addresses a highly innovative and interdisciplinary field that spans automation engineering, metrology, tolerance simulation, and data science. Candidates will have the opportunity to contribute to the scientific advancement of data-driven assembly systems and to actively shape the future of intelligent automotive manufacturing.

Possible Tasks within this Role

• Developing and designing novel automation solutions enabling high‑precision “Best Fit” assembly processes
• Analytically evaluating product and assembly system architectures with a focus on manufacturing tolerances and gap dimension quality
• Formulating data‑driven process and control models for the predictive characterization of component and system behavior
• Designing, programming, and executing experimental test series for the empirical validation of methodological and technological innovations

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, automation engineering, mechanical engineering or a related field of study
• Proficient use of tools and platforms for data analysis, statistical modeling and computational simulation (e.g., Python, MATLAB, database systems, cloud-based data platforms)
• Sound knowledge in machine learning methods and AI-driven process optimization
• Prior experience in robot programming or image processing systems is advantageous
• German language level B2, English language level B1
• Outstanding analytical and conceptual reasoning skills
• Strong teamwork and communication competencies
• Highly structured, autonomous, and scientifically rigorous working style

The following documents must be submitted with the application

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

Keywords

Dissertation, Experimental Methodology, Robotics, Adaptive Manufacturing Control, Cyber-physical Production Systems, Closed-Loop Manufacturing

What we offer

• Attractive salary & 30 vacation days (+ 24.12. and 31.12. off)
• 35-hour week, flexible working hours, remote work
• Special conditions for the purchase and leasing of vehicles
• Free seminars on scientific work and interdisciplinary qualifications
• Participation in the doctoral network for scientific exchange with science representatives and other doctoral candidates within the Volkswagen Group

Contact person for this posting: Fabian Wenzel