Computer Science | Engineering internship: computer vision-based alignment

Introduction

Within the ASML TubeDG multi-disciplinary team, we study and optimize the tin droplet generator's dynamic behavior in order to enable future increases in EUV power. To achieve this, we use vibrometer measurements to reconstruct a 3D harmonic response of key components.  

Your Assignment

In this internship, you will develop a method to align vibrometer measurements using computer vision and machine learning techniques. Vibrometer is an interferometer mounted on a (x,y,z) stage, enabling measurements of 2D harmonic oscillation responses. To extend the capabilities of the setup, a rotary stage has been added. By rotating and recording multiple 2D oscillation responses from different viewing angles, it becomes possible to reconstruct 3D harmonic oscillations of e.g. tubular machine components. However, because the tubular components are not perfectly symmetric and aligned, each rotated measurement requires manual annotation and alignment. This process is time-consuming, subjective and prone to error. The aim of this internship is to replace the manual alignment step with a robust computer vision-based alignment algorithm.
 

The main tasks include:

• Conduct a literature study on relevant computer vision and machine learning methods and evaluate how effective they can be applied for measurement alignment;

• Develop a robust computer vision based algorithm to automatically align vibrometer measurements;

• Perform experimental tests on the vibrometer setup to validate the developed method;

• Improve the accuracy and efficiency of the measurement workflow, including reducing the number of required measurements;

• Document, report and present the methodology, results and conclusions.

This is a Bachelor or Master internship for 5-6 months, working 4-5 days per week (3 days onsite).The topic is also suited for a thesis. The start date of this internship is as soon as possible.

Your Profile

To be a fit for this assignment, you:

• Are busy with your bachelor's or master's in Computer Science or Engineering;

• Possess knowledge of computer vision and machine learning;

• Have some programming experience in Python (OpenCV, NumPy, Tensorflow/Keras) and also MATLAB;

• Have an understanding of or interest in vibration and dynamics;

• Have good communication skills in English (verbal and written).

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).

This position requires access to controlled technology, as defined in the United States Export Administration Regulations (15 C.F.R. § 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

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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