AI-Driven Physical Design Intern (PhD)

Intel Corporation; Boxborough (MA); On-site; USD 142,000 - 143,000; Part time

Job summary

Intel Corporation seeks motivated PhD interns for AI-driven physical design engineering. You will develop AI-powered workflows and data-driven decision making to enhance silicon implementation and design quality.

Join the DCG team to explore Graph Neural Networks, Python-based automation, and ML-driven optimization, while collaborating across AI research and design engineering groups.

Qualifications

• Enrolled in a PhD program in Electrical Engineering, Computer Engineering, Computer Science, or related field.
• Proficiency with RTL design concepts, verification, and industry-standard physical design tools.
• Familiarity with Python or TCL for flow automation and debugging.
• Understanding of Graph Neural Networks (GNNs) or graph-based algorithms.
• Experience with data analysis libraries such as Pandas, NumPy, Matplotlib.
• Knowledge of reinforcement learning concepts for design optimization.
• Strong Python programming skills with ML application experience.
• Background in EDA tools and physical design fundamentals.

Responsibilities

• Research and implement AI/ML techniques to improve physical design processes.
• Develop AI-powered workflows for silicon implementation and design quality.
• Build ML-powered data analysis and summarization pipelines for faster decisions.
• Design and implement GNN-based systems to support intelligent design execution.
• Collaborate with cross-functional AI research and design engineering teams.
• Evaluate AI-driven methodologies against traditional approaches for PPA improvements.

Job description

Intel Corporation seeks motivated PhD interns for AI-driven physical design engineering. You will develop AI-powered workflows and data-driven decision making to enhance silicon implementation and design quality.

Join the DCG team to explore Graph Neural Networks, Python-based automation, and ML-driven optimization, while collaborating across AI research and design engineering groups.