PhD Intern: Process Integration & Yield Engineering

Intel Corporation; Hillsboro (OR); On-site; USD 121,000 - 122,000; Part time

Benefits offered by this job

Stock bonuses

Health benefits

Vacation time

Job summary

Intel Corporation invites talented PhD candidates to join as a Process Integration and Yield Engineering Intern in Hillsboro, Oregon. You will analyze defect data, perform experiments, and refine process integration flows to improve yield in a high-volume manufacturing setting.

Work with cross-functional teams to optimize metrology strategies, apply data-driven insights, and contribute to continuous process improvements.

Qualifications

• Pursuing a Ph.D. in a relevant scientific field and actively enrolled.
• Proficiency in microscopy techniques.
• Knowledge of semiconductor device physics and circuit design.
• Basic scripting skills in Python or comparable languages.

Responsibilities

• Perform defect analysis to identify trends and recommend process adjustments.
• Conduct experiments to evaluate and optimize process integration flows.
• Collaborate with cross-functional engineering teams to troubleshoot process issues and refine metrology strategies.
• Support yield improvement initiatives through risk assessments and data-driven recommendations.
• Apply advanced data analysis techniques to enhance process performance and production efficiency.
• Participate in continuous improvement projects aligned with Intel's business goals.

Skills

Microscopy techniques

Python scripting

Data analysis

Image analysis software

Education

Ph.D. in Chemical Engineering, Physics, EE, Materials Science, or Chemistry

Tools

Python

MATLAB

JMP

Job description

Intel Corporation invites talented PhD candidates to join as a Process Integration and Yield Engineering Intern in Hillsboro, Oregon. You will analyze defect data, perform experiments, and refine process integration flows to improve yield in a high-volume manufacturing setting.

Work with cross-functional teams to optimize metrology strategies, apply data-driven insights, and contribute to continuous process improvements.