Introduction
Within the Materials and Chemistry Group at ASML Research in Veldhoven, you will contribute to advancing knowledge from complex experimental data. Our team uses a wide range of experimental and analytical methods to understand physical phenomena that support future technology development. A key challenge is connecting results from different test environments and understanding how they relate to real-world operating conditions. In this internship, you will explore how Artificial Intelligence and Machine Learning can help bridge these gaps and support data-driven innovation. This Physics | Materials Science internship offers the opportunity to work on meaningful research challenges in a multidisciplinary environment.
Your assignment
As part of this internship, you will investigate how Artificial Intelligence and Machine Learning methods can improve the interpretation of experimental and analytical datasets. You will explore relationships within complex data and evaluate how observations can be translated between different environments and real-world conditions. Working closely with researchers and domain experts, you will combine data-driven approaches with physical understanding to generate valuable insights. Your main responsibilities will be:
- Explore experimental datasets and understand challenges related to comparing different environments
- Evaluate Artificial Intelligence and Machine Learning methods for heterogeneous data analysis
- Develop and assess data-driven models that connect observations across experimental conditions
- Analyze results and identify meaningful patterns and relationships within complex datasets
- Collaborate with researchers from different technical disciplines to interpret findings
- Assess the potential impact of AI-driven knowledge extraction for technology development
- Present conclusions and recommendations through reports and presentations
This is a master's thesis internship for minimum 5/6 months, minimum 4 days per week (Hybrid). The start date of this internship is as of September/October 2026.
Your profile
To be suitable for the internship, you:
- Are pursuing a master's degree in Physics, Materials Science, Applied Physics, Engineering, Data Science, or a related technical field
- Have a strong interest in Artificial Intelligence, Machine Learning, and data-driven modeling
- Have experience with data analysis and programming, preferably using Python or similar programming languages
- Are analytical, proactive, and comfortable working independently while collaborating with others
- Have strong English communication skills, both written and spoken
In addition, you should:
- Be enrolled at an educational institution throughout the entire internship period
- Be located in the Netherlands during the internship, or be willing to relocate
- If applicable, be able to obtain the required university documentation for an internship in the Netherlands
This internship provides significant freedom to explore innovative methodologies and apply them to real-world research challenges. Through this internship, you will gain experience at the intersection of physical sciences, advanced analytics, and technology innovation while contributing to developments that support ASML’s future technologies.
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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