Machine learning internship (non-thesis) for semiconductor metrology

Introduction

Are you a student pursuing a master's in the fields of computer science, machine learning, computer vision, electrical engineering, mathematics and physics. Do you have affinity in Machine Learning and Deep Learning and have a good understanding of Python and MATLAB? Then this internship is for you!

Background Information

ASML is a world leader in the semiconductor manufacturing industry. It's innovative machine stack includes state of the art lithography systems along with cutting edge metrology systems such as Yieldstar. In semiconductor manufacturing overlay is defined as the spatial alignment error between two semiconductor layers. The control of overlay plays an essential role in the optimization of the fabrication yield and profit margin. In this project, you will have the opportunity to interact with various experts on optics and signal processing in the context of YieldStar. The group Image Processing & Machine Learning within ASML caters to a wide range of algorithms focused studies in the domain of wafer metrology. 

Your Assignment

This software engineering internship vacancy comprises of 3 different assignments. The hiring team will assess all applicants and allocate the assignments based on their needs. This will be further discussed during the interview stage.

First assignment:

Title: Robust Pattern Recognition Algorithms for Semiconductor Metrology.

The semiconductor manufacturing loop constantly involves imaging structures with nanometer scale resolution. Among the wide range of algorithms used within ASML machines,  pattern recognition (well-known computer vision algorithm) plays a key component in the processing pipeline. The main goal of this internship assignment is to design and develop next generation pattern recognition algorithms to improve the performance of ASML's metrology systems. Specific tasks will involve designing the signal processing pipeline for physics- and data-driven pattern recognition algorithms. The developed algorithms will be tested on both simulated and measurement data of structures imaged using ASML's Yieldstar system.  The starting point will involve constructing a robust signal processing pipeline on images with partially known target templates. The candidate is expected to perform a detailed and systematic comparison of the current methods (where target template is a hard constraint) with the techniques developed in the project. 

Second assignment

Title: Machine learning (ML) algorithms for optical sensor error correction

The main goal of this internship assignment is to design and develop next generation computational algorithms for sensor correction to eventually improve performance of ASML's metrology systems. This project aims to create machine learning (ML) algorithms for optical sensor error correction. The ML model synthesizes metrology images given specific acquisition settings by learning the pixel-wise relationship within images. The project will involve aspects such as: Preparing a large dataset of metrology images, develop and test (hybrid) ML-based/generative algorithms to characterize metrology systems and compare the performance with traditional approaches.

Third assignment

Title: Next generation motion deblur algorithms for semiconductor metrology The semiconductor manufacturing loop constantly involves imaging structures with nanometer scale resolution. The main goal of this internship assignment is to design and develop next generation computational imaging algorithms (specifically motion deblur) to improve the system performance of ASML's metrology systems. Specific tasks will involve designing the signal processing pipeline for a physics- and data-driven deblur algorithms which can be trained either offline or online. The two key sub components include generative modeling of the expected signal and a learning algorithm for image correction. You will investigate feasibility of image restoration techniques to improve performance of YieldStar where images have motion blur. The starting point will involve constructing the processing pipeline for given (x,y)-position of the moving wafer stage.

Your Profile

To be a perfect match for this internship, you:

• Are a Master student in the field of computer science, machine learning, computer vision, electrical engineering, mathematics and physics.

• Have experience with Signal Processing, Machine Learning, Deep Learning, Hybrid-Machine Learning and Physics Inspired Neural Networks.

• Have a good understanding of Python and MATLAB.

• Have demonstrated an interest in or have experience with hybrid approaches where domain knowledge is incorporated into Machine Learning/Deep Learning models.

• Have great communication skills in English both verbally and in writing.

​This is a Master apprentice internship with a duration of 6 to 12 months, for 4-5 days a week, starting as soon as possible.

Please note that we can only consider students who are enrolled at a school for the entire duration of the internship.

Change the world – one nanometer at a time

Become an intern at a Dutch company that’s a global industry leader. You’ll gain valuable experience in a highly innovative environment – one that sparks your imagination and creativity. In addition to a monthly internship allowance of maximum €600 (plus a possible housing and free public transport), you’ll get practical guidance from experts in the field and the chance to work in and experience a dynamic team environment.

ASML - be part of progress

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. What we do is at the heart of all the electronic devices that keep us informed, entertained and connected. Every day, you use electronics that simply wouldn’t exist without our machines.

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 fields which are not technical oriented.

We believe we can always do better. We believe the winning idea can come from anyone. We love what we do – not because it’s easy, but because it’s hard.

Students - getting ready for real-world R&D

We’re a global team of about 39,000 people of 140 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. 

In such an environment, your colleagues may be sitting next door, or they could be thousands of kilometers away in a different country – or even working for a different company.

An internship at ASML is the opportunity to get to know not only the world of industrial-strength R&D, but yourself – you’ll discover just what excites you most. Will you design a part of the machine, or make sure it gets built to the tightest possible specifications? Will you write software that drives the system to its best performance, or work side-by-side with the engineers of our customers in a fab, optimizing a system to the requirements of the customer?

How will you be part of progress?

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

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.