Electrical Engineering and Data Science Graduation Internship: Improving Temporal Control with Exogenous Data
3 weken geleden
Introduction
Are you a graduating student in Data Science, Physics, Electrical Engineering, Mathematics, or a related field looking for a graduation internship? Do you have experience with signal processing and machine learning, as well as strong programming skills? This internship might be an excellent opportunity for you.
Background Information
Department: BL-Apps MPC D&E PWC Overlay & Alignment, Group: Technology Enablers
Applications Process Window Control On-Product Performance is working on improving customer on-product overlay control performance. This work is part of a roadmap to develop a potential improved temporal control method that may be used in future versions of our control SW products.
Your Assignment
One way to improve on-product overlay is to enhance the time filter used for feedback control. The current state-of-the-art method uses a simple Exponentially Weighted Moving Average to determine the optimal wafer model parameters to correct the next lot. Analysis has shown that using more advanced temporal (prediction) models will not lead to significant improvement. Advice was given to start using exogenous data to enrich the model parameter data and use that to perform predictions.
Examples of exogenous data include:
- Overlay data statistics
- Context data (e.g., etcher chamber IDs)
- Reported scanner data (e.g., reticle alignment parameters, wafer alignment results, exposure timing information)
- Fab logistics information
Work items include writing a test plan, collecting the right data sets, writing tooling for different potential temporal control models, performing proof book analysis, and writing a report.
The goal is to help the overlay control competence in choosing the path to follow with respect to potential future product improvements: do we expect a benefit of changing the way we handle temporal control now? If so, what method(s) show(s) most potential?
Your Profile
To be a perfect match for this internship, you:
- Are a graduating student in Data Science, Physics, Electrical Engineering, Mathematics, or a related field.
- Have a good understanding of either Matlab or Python (or both).
- Have affinity with all or some of the following: signal processing, fourier analysis, machine learning, auto-regression models, Kalman filters, and time-series prediction.
- Are pro-active and capable of working independently.
- Have great communication skills in English, both verbally and in writing.
This is a graduation internship with a duration of a minimum of 6 months, for 4-5 days a week, starting as soon as possible.
Please note that we can only consider students who are enrolled at an educational institution for the entire duration of the internship.
Join a Global Industry Leader
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.
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 that are not technically 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
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
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Veldhoven, Noord-Brabant, Nederland ASML VoltijdIntroductionASML is seeking a graduating student in Data Science, Physics, Electrical Engineering, Mathematics, or a related field to work on improving temporal control using exogenous data. The successful candidate will have a good understanding of signal processing and machine learning, as well as proficiency in programming languages such as Matlab or...
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