In-Device Metrology (IDM) aims at inspecting the quality of the semiconductor patterns, printed in production wafers. This is done by using data-driven mathematical models that relate the physical parameter to the optical signals. The quality of such models is critical to ensure accuracy of the measured parameters. Understanding how optical signals encode physical information enables a better understanding and can help further improve model performance.

Based on measurement data, a model is trained to map high-dimensional optical response to physical parameters of a semiconductor stack. When  is a linear mapping, one can easily visualize  and show which part of the signal has a stronger contribution to physical parameters. However, when  becomes a complex model, for example a neural network. It’s not a trivial task to see which parts of the signal contribute more to a certain physical parameter. Goal of this internship is to build a software tool to visualize and explain neural network models.

Tasks

Investigate the best practices for explainable neural networks such as Saliency map and tailor its implementation for IDM data.

Given 2 trained neural networks, trained with data measured on different sized targets on the wafer, analyze their most contributing features. Find out if overfitting is a problem for certain sized targets.

Given 1 trained CNN model, apply the same analysis as above and report out which features are import and how convolutional kernels are trained to extract them.

To be a match for this internship, you:

Are a (HBO) bachelor student or a master student in Computer Science, Applied Mathematics, Applied Physics or a related field looking for an apprenticeship or a graduation internship.

Have skills in machine learning and are familiar with machine learning tools

Have affinity with physics, metrology and mathematical understanding

Have a can-do mentality and the ability to work independently and collaboratively in a team environment. 

Have effective communication skills and are fluent in English both verbally and in writing. 

​This is a (HBO) bachelor or master apprentice or graduation internship for a minimum duration of 3 months, for 4 to 5 days per week (at least 3 days onsite for full-time). The start date of this internship is flexible.

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.

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.

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