Master Thesis - Machine Learning Techniques for Electrical Circuit Simulation (f/m/div)

Master Thesis – Machine Learning Techniques for Electrical Circuit Simulation (f/m/div)

2 days ago Be among the first 25 applicants

#WeAreIn to create tiny chips and big careers. The future won’t wait… why should you? Join us and make a difference. Whether you join as a student, intern, or trainee, you\’ll be part of something real—real projects, real impact, and real opportunities to grow. Are you in?

Your Role

• Perform simulations of electrical circuits at the system level.
• Develop and evaluate AI‑based algorithms for modeling physical systems.
• Gain practical experience with modern simulation tools and state‑of‑the‑art algorithms and apply them in an industrial environment.
• Document the results and present the research findings to colleagues and management.

Your Profile

• Currently at the end of a master’s degree in Electrical Engineering, Computer Science, Physics or a related field.
• Advanced understanding of machine learning and neural networks as well as circuit simulation methods and electrical engineering.
• Familiar with Python, AI algorithms and preferably also circuit simulation tools.
• Fluent in English; German is a plus.

Application Documents

• CV in English
• Certificate of enrollment at university
• Excerpt of the study regulations for the thesis (if applicable)
• Latest grades transcript (not older than 6 months)
• High school report

Contact

Kerstin Semmler

About Infineon

As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game‑changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. We drive innovation, customer success, and empower our people to reach ambitious goals.

Diversity & Inclusion

We welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to giving all applicants and employees equal opportunities.