EUV Lithography Intern: Research, AI & Process Innovation

Micron Technology, Inc.; Boise (ID); Hybrid; USD 28,000 - 41,000; Full time

Benefits offered by this job

Mentorship

Hands-on projects

Job summary

Micron Technology, Inc. invites applications for an EUV Lithography Intern to join our advanced semiconductor research team. You will design experiments, analyze lithography performance, and contribute to line width roughness improvements alongside multi-functional engineers.

Ideal candidates are pursuing a B.S., M.S., or Ph.D. in engineering or physical sciences and will apply AI-assisted tools to optimize experiments and process data in a fast-paced, collaborative environment.

Qualifications

• Pursuing a B.S., M.S., or Ph.D. in Engineering, Physics, Chemistry, Materials Science, or related photolithography field.
• Must be continuing education through Fall 2027.
• Demonstrated analytical and problem-solving abilities from coursework, research, or projects.
• Strong written, verbal, and presentation communication skills.

Responsibilities

• Design and execute experiments (DOE) to optimize photolithography, including EUV lithography and patterning improvements.
• Plan, coordinate, and support semiconductor process experiments in cleanroom environments.
• Analyze images, metrology results, and process data to evaluate CD, registration, and process capability.
• Communicate technical plans, project status, results, and recommendations through reports and presentations.
• Apply AI and AI-assisted tools to support research, data analysis, and process optimization.

Skills

Analytical skills

Communication skills

Independent worker

Education

Engineering/Physics/ Chemistry/ Materials Science degree

Tools

Python

MATLAB

JMP

R

Job description

Micron Technology, Inc. invites applications for an EUV Lithography Intern to join our advanced semiconductor research team. You will design experiments, analyze lithography performance, and contribute to line width roughness improvements alongside multi-functional engineers.

Ideal candidates are pursuing a B.S., M.S., or Ph.D. in engineering or physical sciences and will apply AI-assisted tools to optimize experiments and process data in a fast-paced, collaborative environment.