Internship in Generative Geometry for Computer Aided Design

Job Description

3D understanding is crucial for the analysis and creation of engineering designs. This is especially challenging for CAD models, which embed not only the object geometry but also the design intent. The goal of this internship is to assist in the creation of AI methods that can automate both geometry understanding and creation.

• During the internship, you will gain hands on experience with latest research about neural representation of geometry, 3D tokenization, and generative modeling (e.g. autoregressive and diffusion).
• You will adapt these techniques or devise novel methods for geometric modeling of engineering design.
• Furthermore, you will create prototypes of AI assistants for engineering tasks.

Qualifications

• Education: studies in the field of Computer Science, Electrical Computer Engineering or comparable
• Experience and Knowledge: solid machine learning foundations; expertise with PyTorch and its ecosystem of GenAI libraries; familiarity with one or more of LLM, diffusion model, 3D deep learning, and CAD is desired
• Personality and Working Practice: driven by curiosity, you contribute to research, effectively communicating complex ideas and presenting technical results clearly
• Languages: fluent in English