AI-Driven Physical Design Intern (PhD)

Intel Corporation; Austin (TX); On-site; USD 142,000 - 143,000; Part time

Job summary

Intel Corporation in the United States seeks an AI-Driven Physical Design Engineering PhD Intern to advance AI-powered workflows for silicon design. The role emphasizes data-driven decision making and adaptive systems to improve execution efficiency.

The internship is part of Intel’s Data Center Group, focusing on high-performance computing and cutting-edge silicon technologies. On-site work in US locations, including Santa Clara and Austin, is expected.

Qualifications

• Enrolled in a PhD program in Electrical Engineering, Computer Engineering, Computer Science, or related field.
• Proficiency with physical design tools (synthesis, place&route, timing analysis).
• Familiarity with Python or TCL for flow automation and debugging.
• Understanding of RTL design and verification.

Responsibilities

• Research and implement AI/ML techniques to improve physical design processes.
• Develop AI-enhanced workflows for silicon implementation.
• Build ML-powered data analysis and summarization pipelines for design decisions.
• Design and implement Graph Neural Network based systems for adaptive design execution.
• Develop automation frameworks using Python and ML libraries (TensorFlow, PyTorch) plus TCL/Perl scripting.
• Collaborate with AI research and design teams to align AI strategies with project goals.
• Benchmark AI-driven methods against traditional approaches to show improvements in PPA.

Skills

PhD mindset

Problem solving

Communication

Team collaboration

Education

PhD student in Electrical Eng./Computer Eng./CS

Tools

Python

TCL

EDA tools

Job description

Intel Corporation in the United States seeks an AI-Driven Physical Design Engineering PhD Intern to advance AI-powered workflows for silicon design. The role emphasizes data-driven decision making and adaptive systems to improve execution efficiency.

The internship is part of Intel’s Data Center Group, focusing on high-performance computing and cutting-edge silicon technologies. On-site work in US locations, including Santa Clara and Austin, is expected.