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INFINEON - Internship – Machine Learning and Data Analytics, SINGAPORE (1 Aug)


Infineon Technologies


Semiconductor Company



Position Type

Internship – Machine Learning and Data Analytics

Post Date

1 Aug 2019

Employer Description

Infineon Technologies AG is a German semiconductor manufacturer founded on 1 April 1999, when the semiconductor operations of the parent company Siemens AG were spun off to form a separate legal entity. As of 30 September 2018, Infineon had 40,100 employees worldwide. In fiscal year 2018, the company achieved sales of €7.599 billion.

Program Details

Job description

In your new role you will:

• Manage data analysis and machine learning model application for false alarm reduction in Abnormality Trigger Project

• Learn and employ machine learning models to support Auto disposition of Lots of Hold and Yield Modelling projects

• Assist key functions in the application of machine learning methods that involve Decision Tree, Bayesian model and K mean clustering

• Be involved in other backend data and analytics projects

Learning outcomes:

• Understand the main steps of back-end assembly packaging process, back-end final test production procedures and the subsequent data post-processing

• Learn the concept and application of Machine learning for back-end assembly and final test

• Gain knowledge on the concept and application of statistical methods for back-end

• Acquire know-how in programming languages through intensive use of batch programming, R, Python and XML language to program a data analysis tool

• Enhance communication skills through interaction with international colleagues


You are best suited for the role if you have:

• On track to attain a Bachelor’s or Master’s degree in Electrical/Electronic Engineering, Computer Engineering/Science or Information Technology, Data Science and Analytics

• Know-how in machine learning and programming languages preferred: R, Python and XML

• Motivated to learn and pick up new knowledge

• This is a minimum 6 months internship opportunity


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