At a glance
- Tools mentioned
- Python
Key facts
- Opportunity type
- Master's thesis
- Organization
- ZEISS
- Location
- Oberkochen, Germany
- Field / discipline
- Technology and Software, Engineering, Energy and Sustainability
- Application deadline
- Deadline not specified — apply early
- Funding / compensation
- Pay not specified
- Duration
- See source description
- Last source check
- 15 Oct 2026
Project 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 RoleWith 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 modelingDevelop modeling approaches for load-driven degradation dataImplement and compare different modeling approaches to identify the most efficient method, taking statistical variation and measurement uncertainty into accountValidate and optimize the developed models through test runs and simulationsPrepare structured documentation of results and present key insights to the project teamYour ProfileEnrolled in a degree program with excellent academic performance in mechanical engineering, electrical engineering, physics, mechatronics or a comparable fieldAcademic focus in technical reliability, modeling, data analysis / data science, or product developmentInitial experience in reliability engineering and programming with Python or MATLABBasic knowledge of data science, modeling, and statistics is an advantageIndependent, solution-oriented and communicative working style Sounds exciting? Then become part of #teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records, etc.).
Your ZEISS Recruiting Team:Verena Hald
Before you apply
0 of 4 readyA preparation checklist, saved in this browser on this device without an account. It does not sync across devices. The official posting determines eligibility and required documents.
How to apply
Apply via zeissgroup.wd3.myworkdayjobs.com. Check the original listing for required documents and submission instructions.
Source and listing information
Application source: zeissgroup.wd3.myworkdayjobs.com. Listing details may change; confirm them on the source site. A source check confirms page availability, not endorsement of the organization.
Report an outdated or incorrect listing