Physics | mathematics | machine learning internship: enhance machine learning frameworks

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Veldhoven
In-Office
Semiconductor
The Role
Introduction

Wafer alignment in TWINSCAN is responsible for correcting wafer deformations and reducing the wafer to wafer lot to lot overlay. Alignment control applications helps users to select the right alignment strategy from all the available options, monitor this alignment strategy through the fab and diagnose any on-product issues coming from alignment.

Your assignment

With increasing options and reducing overlay budget, alignment setup applications enables users to find an alignment strategy resulting in the lowest overlay. Finding such an alignment strategy is an computationally intensive process given the degrees of freedom available in alignment (like models, mark layout, etc.). Currently, we have our machine learning framework to reduce the computational load on our application. In this internship we would like to

  • Extend our ML framework to to train exert assisted cost function/model as a predictor.

  • Minimize the degrees of freedom using data driven optimization algorithms (like Bayesian optimization) in real time.

  • Consider/create framework for utilizing our ML framework and data driven optimization methods to monitor the performance of alignment sub-system in real time at our customer fabs, identify anomalies and provide explanation for said anomalies.

Your profile

To be a great match for this internship you:

  • Are a master student in Physics, Mathematics or a related field with experience/knowledge in machine learning looking for an apprentice or graduation internship.

  • Have knowledge of current Machine Learning/AI framework.

  • Have experience in MATLAB or at least one similar scripting language.

  • Are someone that is flexible, result-driven with an eagerness to learn. You are able to work independently and autonomously.

  • Have strong communication skills and are fluent in English (verbal and written).

This is a master apprentice or graduation internship for a minimum of 6 months, for 4 to 5 days per week (at least 3 days onsite). The start date of this internship is September 2025.

Other requirements you need to meet

  • You are enrolled at an educational institute for the entire duration of the internship;

  • You are located in the Netherlands to perform your internship. In case you are currently living/studying outside of the Netherlands, your CV/motivation letter includes the willingness to relocate;

  • If you are a non-EU citizen, studying in the Netherlands, your university is willing to sign the documents relevant for doing an internship (i.e., Nuffic agreement).

Diversity and inclusion

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 diversity and inclusion is a driving force in the success of our company.

Need to know more about applying for a job at ASML? Read our frequently asked questions.

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The Company
HQ: Veldhoven
34,760 Employees
Year Founded: 1984

What We Do

ASML is a high-tech company, headquartered in the Netherlands. We manufacture the complex lithography machines that chipmakers use to produce integrated circuits, or computer chips. Over 30 years, we have grown from a small startup into a multinational company with over 60 locations across Europe, Asia and the US.

Behind ASML’s innovations are engineers who think ahead. The people who work at our company include some of the most creative minds in physics, electrical engineering, mathematics, chemistry, mechatronics, optics, mechanical engineering, computer science and software engineering.

Because ASML spends more than €2 billion per year on R&D, our teams have the freedom, support and resources to experiment, test and push the boundaries of technology. They work in close-knit, multidisciplinary teams, listening to and learning from each other.

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