The opportunity

Understanding the moisture dynamics in transformer insulation is critical for predicting aging, dielectric failure, and overall
reliability. While recent models like the Thermo-Chemical Digital Twin offer advanced simulation capabilities, one of the main
opportunities for improvement lies in the modeling non-uniform water distribution and its impact on voltage behavior under
transient conditions. Additionally, no established criterion exists for evaluating water content in paper insulation under
energized conditions.

Your responsibilities

• Model Development: Extend the water diffusion model to include spatially resolved moisture dynamics and additional influencing factors such as temperature gradients and oil aging
• Diagnostic Criteria: Develop a practical criterion for evaluating water content in paper insulation under energized conditions
• Voltage Behavior Analysis: Investigate how increased and non-uniform moisture distribution affects voltage response under impulse and switching conditions
• Validation: Validate model improvements through simulations and comparison with Breakdown Voltage (BDV) tests using special wave shapes

Your background

• Master’s student in Electrical Engineering, Power Systems, Applied Physics, or related fields
• Strong foundation in modeling and simulation (e.g., MATLAB, Python, COMSOL)
• Knowledge of dielectric materials and transformer insulation systems
• Analytical and independent working style
• Fluent in English; German is a plus

What we offer

• Supervision by experienced R&D professionals
• Access to internal models, data, and simulation tools
• Opportunity to contribute to cutting-edge transformer diagnostics
• Potential for follow-up opportunities in research or engineering roles
• switching conditions