Work environment

At Volkswagen Group Innovation, we develop AI based tools to accelerate key steps in virtual product development. We work closely with our future transfer partners within the Group brands. The creation and evaluation of 3D geometry through load case simulations represent a significant share of the overall development workload. The use of generative AI and neural surrogate models offers tremendous potential for process acceleration. If you are excited about unlocking this potential within the context of an industrial PhD program, we look forward to receiving your application.

Possible Tasks within this Role

• Building a comprehensive database consisting of real and synthetic CAD/CAE models
• Enhancing AI models for the multimodal generative creation of CAD structures
• Enhancing AI models for the performance prediction of load cases
• Demonstrating the effectiveness of the developed methods using practical examples

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 mechanical engineering, computer science, or a comparable discipline
• Very good programming skills, especially in Python, shell scripting, PyTorch, TensorFlow, and CUDA
• Very good knowledge of computer aided design (CAD), particularly CATIA
• Good knowledge of software development environments such as Linux, Git, and Jira
• German or English language level C1
• Independent and structured working style

Keywords

Dissertation, Surrogate Modeling, Design Engineering, Computational Engineering