Mechanical Engineering | Industrial Engineering internship: reliability data analysis

Introduction

The Quality Engineering & Excellence team within the Reuse & Repair sector focuses on improving the lifetime and reliability of high-value components. You will contribute by analyzing engineering and quality data to understand how reused parts perform over time. This internship helps identify improvement opportunities in repair processes through evidence-based insights. Working alongside experienced engineers, you will support better decision-making using real operational data.

Your assignment

In this role, you will focus on analyzing engineering and quality data rather than building dashboards. You will draw insights from existing data sources and translate them into actionable improvement ideas. Your work will directly support quality engineers in optimizing reuse and repair processes. Your main responsibilities will be

• Perform statistical analysis on repair, quality, and reliability datasets

• Identify trends, correlations, and variation in engineering processes

• Support root cause analysis using structured, data-driven methods

• Evaluate process stability and compare performance across time or products

• Translate complex datasets into clear technical insights and conclusions

• Contribute to improvement proposals based on quantitative findings

• Support technical discussions with concise summaries and data-backed insights

This is a master’s internship (non-thesis) for a minimum of 5 months, a minimum of 24 hours per week (including at least 1 day on-site). The start date of this internship is as of September 2026.

Your profile

To be suitable for the internship, you:

• Are enrolled in a master’s degree in mechanical engineering, industrial engineering, systems engineering, or a related engineering field

• Have experience with data analysis and applied statistics in an engineering context

• Have experience working with data using Excel (required); familiarity with MATLAB, Minitab, or ReliaSoft is a plus

• Demonstrate professional proficiency in English (minimum C1 level), both written and spoken

• Have a clear interest in quality engineering and are analytical, structured, and able to translate complex datasets into clear engineering insights

This position requires access to controlled technology, as defined in the United States Export Administration Regulations (15 C.F.R. § 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

Inclusion and diversity

ASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that inclusion and diversity is a driving force in the success of our company.

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