Master Thesis: AI-Assisted Verification and Review of Electronic Hardware Designs

The increasing complexity of automotive electronics requires efficient methods for design review, verification, and validation. Engineers today spend substantial effort on schematic reviews, creation of verification test cases, and ensuring consistency between requirements, schematics, and PCB implementations. Recent advances in Artificial Intelligence (AI) and Large Language Models (LLMs) offer new possibilities for automating engineering activities and supporting hardware development processes. The purpose of this thesis is to investigate how AI can assist ECAD engineers in their daily work by:

• Reviewing electronic schematics and identifying potential errors, inconsistencies, or design improvements.
• Generating verification and validation test cases based on hardware requirements, circuit descriptions, and netlists.
• Improving schematic readability and quality through automated cleanup, standardization, and documentation support.
• Evaluating how AI-generated results compare with traditional engineering review methods.
• Exploring opportunities and limitations of applying AI in automotive hardware development.

- Expected outcome The thesis is expected to provide

• A structured evaluation of how AI can support schematic reviews and hardware verification activities.
• Methods for automatically generating test cases from requirements and circuit information.
• Recommendations for improving schematic quality through AI-assisted standardization and review processes.
• An assessment of the benefits, limitations, and practical applicability of AI within automotive electronics development.
• Insights into future opportunities for integrating AI into ECAD engineering workflows.

Qualifications You are a curious and motivated student with a strong analytical mindset and an interest in solving complex technical problems. You enjoy taking initiative, working independently, and exploring new technologies. To be successful in this thesis project, we believe that you have:

• Ongoing Master's studies in Electronics, Electrical Engineering, Computer Engineering, Engineering Physics, Computer Science, AI, or a related field.
• An interest in programming, AI, Machine Learning, or Large Language Models.
• Basic knowledge of electronics, hardware design, or circuit analysis gained through your studies.
• An interest in electronics development and verification.
• Curiosity about new technologies and their practical applications.
• Strong analytical thinking and a structured approach to solving technical challenges.
• Good communication skills in English, both written and spoken.

Application and Contact Information If you have any questions regarding the thesis project, please contact Talent Acquisition Partner Per Lind at per.lind@magna.com or Supervisor/Manager Per Holmberg at per.holmberg@magna.com. Last application date: 2026-10-15. P lease note that we review applications on an ongoing basis and the position may be filled before the application deadline. Start: Spring 2027, 30 p Master's Thesis Number of Students: 1-2 Want to learn more about Magna, our operations in Sweden, and how we work with recruitment, onboarding, and employee development? Visit Our Career Page https://www.magna.com/careers/sverige Awareness, Unity, Empowerment At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law. Worker Type Student / Co-Op Group Magna Electronics