Within this project at KAI the thermo-mechanical fatigue of Cu power metallization will be analyzed. To achieve this, a pulse generator which tailors the profile of the applied electrical pulses needs to be implemented into an existing setup. Additionally, a python-based evaluation workflow should be optimized to perform data processing and evaluation of synchrotron X-ray diffraction data. Education: Pursuing a Master's degree in Materials Science, Physics, Computer Science, or Mechanical Engineering, having finished study exams and ready to start working on the thesis Technical Skills: Knowledge and experience in programming via Python and/or LabVIEW Language Skills: Fluency in English and/or German Problem-Solving: Hands-on mentality with a strong ambition for method development and bringing ideas to life Teamwork: Ability to work effectively with an international team We are on a journey to create the best Infineon for everyone. This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills. Knowledge Acquisition: Learn about the concepts of thermo-mechanical fatigue testing, programming via Python and LabVIEW, and the basics of scanning electron microscopy (SEM) System Development: Use LabVIEW and Python programming to implement a new power switching setup into the current thermo-mechanical fatigue test system Research and Analysis: Study the impact of different pulses on the thermo-mechanical fatigue of Cu metallization via SEM characterization, and advance an existing Python-based evaluation workflow to evaluate time-resolved X-ray diffraction data Documentation and Thesis: Document results by writing and submitting a Master's thesis
