PhD Student Manufacturing Variations Control - Best-fit Assembly

• 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

• 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

Prior experience in robot programming or image processing systems is advantageous

• 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