AI-Powered Physical Design PhD Intern

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

Benefits offered by this job

Stock bonuses

Health benefits

Retirement plan

Vacation

Job summary

Intel Corporation is seeking an AI-Driven Physical Design Engineering PhD Intern to leverage AI/ML for silicon physical implementation. You will develop AI-powered workflows, build data analysis capabilities, and design adaptive systems to enhance execution efficiency and data-driven decision making.

Based in the US, you will collaborate with the Data Center Group and cross-functional teams to benchmark AI approaches against traditional methods, driving measurable improvements in Power,

Qualifications

• Enrolled in a PhD program in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Familiarity with scripting languages like 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 high-performance silicon implementation.
• Build ML-powered data analysis pipelines for faster design decisions.
• Design Graph Neural Network based systems to support intelligent design execution.
• Develop automation frameworks using Python and ML libraries (TensorFlow or PyTorch) alongside TCL/Perl.
• Collaborate with cross-functional AI research and design teams to align AI strategies.
• Benchmark AI-driven methods against traditional approaches to improve PPA.

Skills

Problem solving

Teamwork

Communication

Education

PhD candidate in Electrical Engineering / Computer Engineering / Computer Science

Tools

Synthesis tools

Place & Route tools

Timing analysis software

Job description

Intel Corporation is seeking an AI-Driven Physical Design Engineering PhD Intern to leverage AI/ML for silicon physical implementation. You will develop AI-powered workflows, build data analysis capabilities, and design adaptive systems to enhance execution efficiency and data-driven decision making.

Based in the US, you will collaborate with the Data Center Group and cross-functional teams to benchmark AI approaches against traditional methods, driving measurable improvements in Power,