Magnet.me  -  The smart network where students and professionals find their internship or job.

The smart network where students and professionals find their internship or job.

Computer science | data science internship: AI foundation model for estimation & control

Posted 24 Nov 2025
Share:
Work experience
0 to 2 years
Full-time / part-time
Full-time
Job function
Degree level
Required language
English (Fluent)
Start date
1 February 2026

Build your career on Magnet.me

Create a profile and receive smart job recommendations based on your liked jobs.

Be part of progress: Join ASML’s Applied Data Science Team

Introduction

Join ASML’s Applied Data Science team, where we develop AI and machine learning solutions that improve the performance and reliability of advanced lithography systems. Our work combines technical expertise with domain knowledge to create data-driven algorithms for calibration, diagnostics, and predictive maintenance. This internship will contribute to exploring cutting-edge transformer models for in-context learning, helping optimize control-loop input estimation in ASML machines. If you are passionate about AI and want to apply your skills to real-world challenges, this is your opportunity. 🚀

Your assignment

You will investigate how pretrained transformer models can perform in-context learning (ICL) for interpolation and control-loop input estimation in lithography systems. The goal is to evaluate and fine-tune models to improve predictive accuracy and decision-making in production processes.

  • Analyze transformer architectures and their ICL capabilities for ASML-specific processes.
  • Fine-tune models on diverse datasets to enhance domain-specific performance.
  • Integrate multiple data sources to build robust predictive models.
  • Validate results with domain experts and document findings.
  • Deliver well-structured, maintainable code for future use.
  • Summarize insights and propose improvements for model deployment.

This is a master’s thesis internship for a minimum of 6 months, 5 days per week (3 days on-site). The start date of this internship is as of February 2026.

Your profile

To be suitable for the internship, you:

  • Are enrolled in a master’s degree in computer science, data science, applied mathematics, or applied statistics.
  • Have strong knowledge of deep learning frameworks (e.g., PyTorch) and Python programming.
  • Understand natural language processing and have experience with related projects.
  • Are analytical, proactive, and able to work independently.
  • Communicate effectively in English (both spoken and written) and are able to explain technical data to the team.

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

About ASML

ASML is a leading supplier of lithography equipment, used by the world’s top chipmakers to print microchips that are increasingly powerful, fast and energy efficient. We’re a global team of more than 32,000 people from 122 different nationalities and counting. Headquartered in Europe’s top tech hub, the Brainport Eindhoven region in the Netherlands, our operations are spread across Europe, Asia and the US.

We're moving technology forward
In fact, we’re probably a part of the electronic device you’re using right now. Our lithography technology is fundamental to mass producing semiconductor chips. With it, the world’s top chipmakers are creating microchips that are more powerful, faster and energy efficient.

Engineering
Veldhoven
Active in 16 countries
42,000 employees
70% men - 30% women
Average age is 38 years