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Master Thesis Reliability(m/w/x)
Developing load-driven degradation models for semiconductor manufacturing equipment. Python or MATLAB programming experience required. Work on state-of-the-art reliability methods in a technology leader.
Anforderungen
- Enrolled in degree program, excellent academic performance in mechanical engineering, electrical engineering, physics, mechatronics, or 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
Aufgaben
- Familiarize with state-of-the-art reliability modeling methods
- Develop modeling approaches for load-driven degradation data
- Implement and compare various modeling approaches
- Consider statistical variation and measurement uncertainty
- Validate and optimize models through test runs and simulations
- Prepare structured documentation of results
- Present key insights to the project team
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- MATLAB
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Master Thesis Reliability(m/w/x)
Developing load-driven degradation models for semiconductor manufacturing equipment. Python or MATLAB programming experience required. Work on state-of-the-art reliability methods in a technology leader.
Anforderungen
- Enrolled in degree program, excellent academic performance in mechanical engineering, electrical engineering, physics, mechatronics, or 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
Aufgaben
- Familiarize with state-of-the-art reliability modeling methods
- Develop modeling approaches for load-driven degradation data
- Implement and compare various modeling approaches
- Consider statistical variation and measurement uncertainty
- Validate and optimize models through test runs and simulations
- Prepare structured documentation of results
- Present key insights to the project team
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- MATLAB
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Carl Zeiss SMT GmbH
Branche
Manufacturing
Beschreibung
Das Unternehmen ist Technologieführer im Bereich Halbleiterfertigungs-Equipment und ermöglicht die Herstellung von leistungsfähigeren und energieeffizienteren Mikrochips.
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