Applied Physics Internship: Data Science and Image Processing SEM Metrology

Position: Applied Physics Internship: Data Science and Image Processing for SEM Metrology
Applied Physics Internship:
Data Science and Image Processing for SEM Metrology  Veldhoven
WO
Full-time
In a nutshell

Location:

Veldhoven, Netherlands
Team:  Interns and Trainees

Work experience:

See job description
Educational background:  Physics
Travel:  No
Programming languages:  Python
Workplace type:  On-Site
Introduction  The Wafer Metrology group is part of ASML’s Development & Engineering organization, within the Performance & Integration cluster. The group is responsible for developing a robust metrology ecosystem that enables accurate performance assessment and optimization of ASML’s lithography systems. This ecosystem includes state-of-the-art hardware platforms—such as Critical Dimension Scanning Electron Microscopes (CD-SEM) and optical metrology tools—as well as advanced software solutions for image processing, contour extraction, and KPI evaluation.
CD-SEM is a cornerstone technology in semiconductor manufacturing and is widely used across both Research & Development (R&D) and High Volume Manufacturing (HVM) to monitor lithographic fidelity, process stability, and yield‑critical phenomena such as defects.
Your assignment  We are offering three internship assignments, each focusing on a key challenge in SEM imaging.
Assignment 1:
Defect Detection & Classification in CD-SEM Images
Defects in CD-SEM images can significantly impact metrology accuracy and process performance. At the same time, they provide valuable insight into process behavior. In this internship, you will develop scalable algorithms to detect and classify defects in large SEM datasets. You will categorize defects (e.g., bridging, breaks, deformations) and analyze their impact on key lithography metrics such as CD, LER, and LWR.

You will also design strategies to identify or filter defect‑corrupted measurements to improve metrology robustness.
Assignment 2:
Automated & Robust Denoising of CD-SEM Images
SEM images inherently contain noise, which propagates into contour extraction and affects measurement precision. Current denoising approaches often require manual tuning, limiting scalability. In this internship, you will develop automated and adaptive denoising methods that minimize noise while preserving critical pattern details. You will analyze SEM noise characteristics and design algorithms (e.g., filtering, model‑based, or data‑driven) that can operate robustly across varying conditions.

The solution should be scalable and suitable for high‑volume manufacturing environments.
Assignment 3:
Data-Driven 3D Profile Extraction from Top‑Down SEM Images
Understanding 3D feature geometry is critical for next‑generation semiconductor devices, yet SEM images provide only 2D information.
In this internship, you will explore machine learning approaches to infer 3D structural information from top‑down SEM images. You will extract meaningful image features, align SEM data with ground‑truth measurements (e.g., AFM), and develop predictive models (e.g., CNNs or regression models) to estimate 3D parameters such as height and sidewall angle. You will evaluate model performance across different patterns and conditions.
This is a bachelor/master internship for a minimum of 5-6 months, minimum 3 days per week (3 days on‑site). The start date of this internship is as of September 2026, but flexible.

Your profile   To be suitable for the internship, you:
Are pursuing a bachelor’s (WO) or master’s degree in applied physics, physics, engineering or similar.
Have a background in image processing, machine learning, and/or data science.
Have

Experience with Python and relevant scientific libraries.
Have strong analytical and problem‑solving skills.
Have good communication skills and ability to present technical results.
Have familiarity with semiconductor manufacturing or metrology (considered a plus).
Other requirements you need to meet:
You are enrolled at an educational institute for the entire duration of the internship;
Attach your cover letter with a clear motivation why you are interested in this internship assignment in particular;
You need to be located in the Netherlands to perform your internship. In case you are currently living/studying outside of the Netherlands, your CV/motivation letter needs to include 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).
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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