Put the skills you have acquired during your studies into practice and complete your final thesis with us. To optimize service and ensure operational reliability, it is essential to be able to reliably estimate the service life of all components. Power electronics are exposed to various influences during operation that affect the service life of the components. The predictive maintenance approach allows to optimize maintenance intervals by the information extracted from the device, a digital model and a database. Literature research, overview of the state of the art Investigation of UPS topology and determination of characteristics for lifetime estimation of critical components. Implementation of data storage and transmission from the UPS Creation of a model for lifetime prediction of the investigated components based on the measured characteristics from the UPS Investigation of AI algorithms to improve lifetime prediction Goal: Lifetime prediction of critical components in the UPS system Ability to work in a team and good communication skills Ongoing studies with a focus on electrical engineering Openness and flexibility to challenges Ability to organize independently Ability to work independently and conscientiously Experience with simulation tools like Matlab or Octave Knowledge in microcontroller programming An innovative, global company that combines tradition with modernity A modern team We deal with the future technologies of tomorrow, with your work you can help shape them in a groundbreaking way Exciting tasks in the field of energy supply (from classic areas to the energy transition) Excellent working atmosphere and adequate space for your ideas; it is explicitly desired that you contribute actively A positive welcome culture and excellent induction by our experienced colleagues Large canteen with a wide selection on the company premises Fruit and water are always available free of charge