Master Thesis: Feasibility study on machine learning techniques for image data

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Master Thesis: Feasibility study on machine learning techniques for image data

At a glance

The combination of image processing techniques with machine learning methods provides powerful tools for automated image classification. In production, different images are captured at different stages of production, providing an insight into the quality of the processes. Although a high level of automation has already been achieved, there are still challenges and manual interaction is still required on a day-to-day basis. These arise, for example, from the resolution of images or a variety of recording options, where adjustments to the tool or the corresponding selection of different analysis methods are necessary. In particular, we need to develop a process or method for the automated classification of defects from defect density images generated during production. In order to successfully apply these methods, not only a large amount of data is required, but also data pre-processing to ensure high data quality. In most machine learning projects, data acquisition and pre-processing is laborious and requires up to 80% of project resources. However, this is an important pre-processing step to successfully apply machine learning techniques. That's why we need your support.

Quick info



Entry level

0-1 year

Job ID





Part time



Job description

In your new role you will:

  • Perform a literature study on classical image processing methods and machine learning techniques applied to image data
  • Perform state-of-the art analysis on image classification methods, used within the semiconductor industry
  • Take images in the fab and make a manual assessment for image labeling
  • Exchange about available and gained knowledge with internal experts
  • Perform a feasability study and identify bottlenecks with regards to setting up an image classification procedure
  • Attempt a first automated classifier demo
  • Document your achieved results

Start: immediatly
Durtion: part time


You are best equipped for this task if you:

  • Study mathematics, statistics, physics, data science, computer science or comparable
  • Have experience in image processing or machine learning
  • Are interested in the investigation of image data by applying image processing / machine learning methods
  • Have programming skills e.g. in R, Python, Matlab
  • Have knowledge of Microsoft Excel (incl. Makros)
  • Are willing to take images in the production line and to manually label them
  • Are fluent in German and /or English (written and spoken)

This position is subject to the collective agreement for workers and employees in the electrical and electronics industry. Master students receive a compensation of 2.210,-- Euro gross p.m. (full-time basis).

Please attach the following documents to your application:

  • Motivation letter
  • CV
  • Copy of your Certificate of matriculation at a university
  • Copy of your Transcript of records
  • Copy of the highest completed educational certificate (Bachelor certificate for Master students)

About Us

Part of your life. Part of tomorrow.

We make life easier, safer and greener - with technology that achieves more, consumes less and is accessible to everyone. Microelectronics from Infineon is the key to a better future. Efficient use of energy, environmentally-friendly mobility and security in a connected world - we solve some of the most critical challenges that our society faces while taking a conscientious approach to the use of natural resources.

*The term gender in the sense of the General Equal Treatment Act (GETA) or other national legislation refers to the biological assignment to a gender group. At Infineon we are proud to embrace (gender) diversity, including female, male and diverse.

Contact Us

Julia Gabriel

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