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Working Student: Machine Learning for semiconductor layouts (f/m/div) at Infineon Technologies AG Australia

Munich, Bavaria, Germany -

Full Time

Start Date

Immediate

Expiry Date

12 Feb, 26

Salary

0.0

Posted On

15 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Semiconductor Design, Data Analysis, Communication, Documentation, Teamwork, Curiosity, Proactivity

Industry

Semiconductor Manufacturing

Description

Study field: You are currently studying Computer Science, Electrical Engineering, Physics, Mathematic or similar Skills: You are familiar with programming in Python and applying basic machine learning concepts to real-world data Interests: You have an interest in semiconductor design data and are eager to learn how layout structures and design rules influence product quality and reliability Way of working: You communicate clearly, document thoughtfully, and can translate technical details into practical next steps Personality: You are proactive, curious, enjoy working in a team, and are good at dealing with a wide range of opinions and turning ambiguities into tangible results Language skills: You have good and English skills, both written and spoken; German is a plus Infineon´s Quality Management department acts proactively to satisfy the needs of our customers to increase their success and to ensure 'best in class' product quality. Internally the department develops a living quality culture at all levels within the different divisions and at our partners. We are on a journey to create the best Infineon for everyone. This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills. Working part-time: The focus is on studies.

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Responsibilities

The role involves applying machine learning concepts to semiconductor layout data. You will learn how layout structures and design rules influence product quality and reliability.