Your tasks
Theoretical Part:
• Get an understanding of what defect data is and how it can be handled.
• Comprehensive literature review of state of the art usage of defect data within semiconductor industry (yield prediction, signature prediction, defect classification etc.).
• Literature review of possibly already existing models incorporating defect data.
• Evaluation of approaches to establish yield predictions with defect data
Practical Part:
• Close cooperation with various departments (Defect, IT, Product Engineering etc.)
• Understand defect classification/categorization
• Get actual state of available data and its usage
• Define possible solutions for the problem statement
Who we are looking for
• Completed Bachelor’s degree in data science or comparable
• Experience in Machine Learning and/or Artificial Intelligence
• Experience in semiconductor environment beneficial
• Independent and structured way of working
We offer competitive salaries and additional benefits based on your performance, experience, and qualifications. Employment is in accordance with the collective agreement for the electrical and electronics industry, employment group E (https://www.feei.at/aktuelles/mindestloehne-und-gehaelter-eei/).




















