Master Thesis: Advancing Ion Beam Tuning Prediction in Semiconductor Manufacturing

Explore the cutting-edge realm of semiconductor manufacturing! Your thesis will revolve around ion implantation equipment. Your mission: develop an AI model that goes beyond predicting just the subsequent tuning outcome, foreseeing multiple upcoming tunings.

Your Challenge

In semiconductor manufacturing, ion beam tuning is critical for each process specification change at implantation.1 The key to success lies in avoiding costly timeouts caused by unsuccessful tuning. As part of your thesis, you’ll work on an AI prediction model that estimates the tuning outcome for the consecutive implantation process as the first step. Building on this model, the final goal is to extend it to predict outcomes for multiple upcoming tunings.

Deep Learning in Focus

Over the course of an 8–12-month internship, you’ll dive into the realm of deep learning models. Within a team of master and PhD students, you will be developing cutting-edge techniques that empower predictive maintenance, revolutionizing semiconductor processes.

Your Profile

As a passionate computing and data enthusiast, you’re the perfect candidate for this exciting challenge. Your solid experience with Python, including scikit-learn and TensorFlow/Keras/Pytorch, makes you wellprepared for the task. Fluency in written and spoken English is essential, with German language skills as a plus. While not mandatory, familiarity with SQL will be advantageous. The ability to query data from databases will enhance your exploration of predictive insights.

Join the Frontier of Ion Beam Tuning Prediction!

Embrace the opportunity to be at the forefront of semiconductor advancements. Your contributions to developing an AI model that predicts multiple upcoming tunings will shape the future of manufacturing.

Our company offers a flexible work environment, allowing remote work from home. Employees can also dedicate office hours to academic pursuits, including thesis writing. Join us to thrive personally and professionally.

This position is subject to the collective agreement for workers and employees in the electrical and electronics industry (full-time), employment group D (basic level) for master students:


Preferred start date: October 2023

Please attach the following documents (German or English) to your application and send it to andreas [dot] laber [at] infineon [dot] com:

  • CV
  • Letter of motivation
  • Certificate of matriculation in a master program at a university
  • Latest transcript of records (not older than six months)


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