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

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What we offer:

At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.

Group Summary:

Transforming mobility. Making automotive technology that is smarter, cleaner, safer and lighter. That’s what we’re passionate about at Magna Electronics, and we do it by creating world-class Electronic systems. We are a premier supplier for the global automotive industry with full capabilities in design, development, testing and manufacturing of complex Electronic systems. Our name stands for quality, environmental consciousness, and safety. Innovation is what drives us and we drive innovation. Dream big and create the future of mobility at Magna Electronics.

Job Responsibilities:

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 [email protected] or Supervisor/Manager Per Holmberg at [email protected].

Last application date: 2026-10-15.

Please 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.

AI-Assisted Screening Disclosure

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.

If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.

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