AI-Driven EUV Mask R&D Engineer

Micron Technology, Inc; Boise (ID); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Health insurance

Paid time off

Holiday pay

Job summary

Micron Technology, Inc in Boise, Idaho is seeking an EUV Mask Technology FEOL RND Engineer. You will develop AI-assisted EUV mask blank materials and processes, optimize lithography performance for High-NA EUV, and translate lithography requirements into manufacturable mask solutions with cross-functional OPC and design teams.

The role involves data-driven R&D to improve yield, reliability, and manufacturability, collaborating with cross-functional teams to transition new technologies into FEOL

Qualifications

• MS or PhD in Materials Science, Physics, Chemistry, Chemical Engineering, or related field.
• Minimum 2+ years in semiconductor manufacturing, process development, or related academic research.
• Experience with EUV/High-NA EUV mask, lithography, or wafer fabrication is preferred.

Responsibilities

• Develop AI-assisted EUV mask blank materials and processes, including film stack design and patterning.
• Advance High-NA EUV readiness through material selection, mask design, stitching, and lithography optimization.
• Translate lithography requirements into manufacturable mask solutions with OPC and design teams.
• Conduct data-driven R&D using DOE and analysis to improve yield and manufacturability.
• Collaborate with cross-functional teams to transition new technologies into FEOL process engineering.

Skills

Data analysis

Collaboration

Communication

Problem solving

Education

MS or PhD in Materials Science, Physics, Chemistry, Chemical Engineering, or related field

Job description

Micron Technology, Inc in Boise, Idaho is seeking an EUV Mask Technology FEOL RND Engineer. You will develop AI-assisted EUV mask blank materials and processes, optimize lithography performance for High-NA EUV, and translate lithography requirements into manufacturable mask solutions with cross-functional OPC and design teams.

The role involves data-driven R&D to improve yield, reliability, and manufacturability, collaborating with cross-functional teams to transition new technologies into FEOL