Req. ID : 142681
Title of project : Virtual metrology modelling based on image data from wafer inspection systems
Description : In semiconductor manufacturing virtual metrology refers to methods to predict the properties of a wafer based on machine parameters and sensor data in the production equipment, without performing the (costly) physical measurement of the wafer properties.
Water inspection systems (WIS) are installed in many of the latest semiconductor equipment and these are used to capture high resolution images of wafers after various process steps.
This image data is relatively inexpensive and available for all wafers as opposed to conventional metrology and can be used to predict physical measurements.
In this project you will build machine learning models to predict metrology data using wis image data.
Scope : Collaborate with experienced process control engineers and process owners to understand specific process control and monitoring requirements that can be met by virtual metrology.
Learn and apply latest machine learning / deep learning techniques to build robust predictive models.
Deliverable : Create a framework to build, score and maintain repeatable WIS based Virtual metrology models. Deploy a Virtual metrology model for production use.
Recommended qualifications : Computer Engineering / Electrical Engineering
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
For US Sites Only : To request assistance with the application process and / or for reasonable accommodations, please contact Micron’s Human Resources Department at 1-800-336-8918 or 208-368-4748 and / or by completing our General Contact Form
Keywords : Singapore North West (SG-03) Singapore (SG) Frontend Manufacturing Intern Internship Engineering #LI-IT1 Tier 1