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Intern - Analytics/Modelling Engineer

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The Programme

Translate your education and talent into a career fueled by possibilities. Develop your skills and expand your opportunities with access to the industry's leading talent, training, and technology. You’ll be contributing your expertise to help reshape information, communication, and innovation around the globe.

Innovation is the lifeblood of our business. Our ability to compete and win in the memory market depends on a free flow of ideas and perspectives at all levels of the business. Inclusion allows creativity and innovation to thrive and empowers us to make the best decisions for all our people and our company.

At Micron, our people are our most important resource and a critical driver of our competitive advantage. We believe our best innovation springs from our team members' diverse experiences, perspectives and backgrounds. We are passionate about creating a diverse and inclusive environment, representative of our communities and the customers we serve.

What You Will Do

Title of Project:

Virtual metrology modelling based on image data from wafer inspection systems.


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.


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 the latest machine learning/deep learning techniques to build robust predictive models.


Create a framework to build, score and maintain repeatable WIS based Virtual metrology models. Deploy a Virtual metrology model for production use.

Required Skills and Abilities

  • Recommended qualifications - Computer Engineering / Electrical Engineering.
Closing in 18 days
Closing in 18 days
  • Job type:Internships
  • Disciplines:


  • Citizenships:

  • Locations:

    Singapore (Singapore)

  • Closing Date:13th Jun 2020, 6:00 pm


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