Machine Learning for Electronics Design Automation - Internship

Description

• Work on low-TRL research projects.
• Create academic publications.
• Develop demonstrators and participate in technology transition to business.
• Contribute to the task of developing machine learning algorithms for electronics design automation.
• Work with Siemens software products (e.g., Calibre, Tessent, etc.) to develop demonstrators and participate in technology transition to Siemens’ businesses.
• Work on fast-paced co-creation projects with quickly changing requirements in the field at the intersection of machine learning and EDA.
• Work on the task of accelerating physical design, testing, and verification using AI/ML techniques.
• Create technical reports.

Requirements

• Familiar with integration of graph neural network for EDA applications.
• Research specialization in graph neural networks and generative models.
• Research specialization in the application of AI/ML for EDA.
• PhD students (currently enrolled in school) in Electrical Engineering, Computer Science, or other from an accredited university.
• Research specialization in the field of physical verification and design for testing.
• Proficiency in English both written and verbal
• Proficiency in python, PyTorch and PyG.
• Legal authorization to work in the United States without corporate sponsorship now or in the future.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance