Computer Science | Data Science internship: optimization & control alghorithms

Introduction

The Product Alignment team in Business Line Applications develops solutions that help ASML systems achieve accurate wafer positioning. The group focuses on alignment control products that support high‑performance patterning in advanced semiconductor manufacturing. As requirements in the industry grow, wafer behavior, process noise, and measurement uncertainty make alignment increasingly challenging. These trends create new opportunities for machine learning and advanced optimization. In this internship you contribute to exploring next‑generation strategies for accurate and efficient wafer alignment.

Your assignment

In this internship, you investigate how machine learning, statistical modeling, and optimization can improve alignment performance. You work with experts to understand the current alignment pipeline and propose new algorithmic approaches that enhance accuracy, robustness, or computational speed. The assignment combines research, prototyping, and evaluation of algorithmic concepts for real‑world use cases. Your main responsibilities will be:

• Explore data‑driven methods that address wafer variability, noise, and measurement uncertainty.

• Develop and test new algorithms that improve accuracy or computational efficiency.

• Analyze real or simulated alignment data to evaluate algorithm performance.

• Design and compare modeling or optimization strategies for key alignment challenges.

• Collaborate with domain experts to refine problem statements.

• Translate research insights into practical prototypes or demonstrators.

• Present results and recommendations for potential next steps.

This is a bachelors/master’s (thesis ) internship for a min 6 months but

preferably 9 months, 4–5 days per week (at least 2 days on‑site). The start date of this internship is September 2026.

Your profile

To be suitable for the internship, you:

• Are a bachelor's/master’s student in applied physics, electrical engineering, systems and control, computer science, mathematics, or a related field.

• Have strong knowledge of machine learning, optimization algorithms, and algorithm evaluation.

• Are skilled in Python or MATLAB; other programming languages are beneficial.

• Are analytical, proactive, and eager to learn in a complex technical environment.

• Have experience with data analysis, modeling, or algorithm development.