ZEISS
semiconductor manufacturing
MasterThesisReliability(f/m/x)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Master Thesis Reliability (f/m/x) at ZEISS. Skills: Reliability modeling, Python, MATLAB. Familiarize with reliability modeling methods. Develop modeling approaches for data”
Industry & Context.
Solution-oriented
What They're Looking For.
Must Have
Enrolled in a degree program with excellent academic performance in mechanical engineering, electrical engineering, physics, mechatronics or a comparable field, Academic focus in technical reliability, modeling, data analysis / data science, or product development, Initial experience in reliability engineering, Programming with Python or MATLAB
Nice to Have
Basic knowledge of data science, Basic knowledge of modeling, Basic knowledge of statistics
What You'll Do.
Familiarize with reliability modeling methods
Develop modeling approaches for data
Implement and compare modeling approaches
Validate and optimize models
Prepare documentation of results
How You'll Work.
Team & Collaboration
Present key insights to the project team
Full Job Description
Enabler for smaller, more powerful, and more energy-efficient microchips Working for tomorrow today. Around 80 percent of all microchips worldwide are produced using ZEISS technologies. As the centerpiece of every electronically controlled system, they have become an integral part of our everyday lives – whether in smartphones, smart homes or smart factories. ZEISS is a technology leader in the field of semiconductor manufacturing equipment. With high-precision lithography optics, photomask systems and process control solutions, ZEISS enables the production of ever smaller, increasingly powerful, and more energy-efficient microchips, and thus plays a pivotal role in the age of micro- and nanoelectronics. # **Your Role** With us, you have the opportunity to perfectly combine your studies with practical experience while actively contributing to exciting projects. This allows you to gain valuable skills, expand your network, and grow both professionally and personally. * Familiarize yourself with state-of-the-art methods in reliability modeling * Develop modeling approaches for load-driven degradation data * Implement and compare different modeling approaches to identify the most efficient method, taking statistical variation and measurement uncertainty into account * Validate and optimize the developed models through test runs and simulations * Prepare structured documentation of results and present key insights to the project team # **Your Profile** * Enrolled in a degree program with excellent academic performance in mechanical engineering, electrical engineering, physics, mechatronics or a comparable field * Academic focus in technical reliability, modeling, data analysis / data science, or product development * Initial experience in reliability engineering and programming with Python or MATLAB * Basic knowledge of data science, modeling, and statistics is an advantage * Independent, solution-oriented and communicative working style Sounds exciting? Then become par
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