Graduation assignment: Finding patterns in scanner data for wafer output optimization
Computer Science & Software Engineering
In a nutshell
No experience (Student)
Data Science, Computer Science & Software Engineering, Mathematics
Are you curious about searching and finding the pros and cons of the High Performance Cluster and KNIME software in collaboration with ASML employees to build machine learning models? Then this graduation assignment could be interesting for you.
ASML designs, develops and integrates markets and services with advanced Photolithography systems used by customers – the major global semiconductor manufacturers – to create chips that power a wide array of electronic, communications and information technology products; These machines produce big amounts of data, whose RequisitionLocal is only possible using Data Science.
You will learn the software KNIME – namely KNIME Analytics Platform, KNIME Server and KNIME Web portal - to apply machine learning algorithms to scanner logging. Your study will demonstrate the benefit of machine learning for scanneroutput optimization. This is a practical exercise as it will be applied on scanner data used by our customer support. You will make use of machine learning & pattern recognition to find output optimal scanner settings for our customers.
The assignment will include:
1.Getting familiar with ASML scanner productivity loggings
2.Combine various data sources from various machines and apply machine learning/pattern recognition techniques to it.
3.Search for relations/patterns in the logging than can improve scanner output.
4.Write thesis report
You are a Master’s student with a background in Computer Science, Mathematics or Data Science and have a big data problems background. You also are interested in the practical aspect as your work will be applied to customer data. Basic programming skills are required. You are driven to produce a new solution to the highest quality standards.
This is a graduation assignment for 5 days a week with a minimum duration of 6 months.
Please keep in mind that we can only consider students (who are enrolled at a school during the whole internship period) for our internships and graduation assignments.
What ASML offers
Your internship will be in one of the leading Dutch corporations, gaining valuable experience in a highly dynamic environment. You will receive a monthly internship allowance of 500 euro (maximum), plus a possible housing or travel allowance. In addition, you’ll get expert, practical guidance and the chance to work in and experience a dynamic, innovative team environment.
ASML: Be part of progress
We make machines that make chips – the hearts of the devices that keep us informed, entertained and safe; that improve our quality of life and help to tackle the world’s toughest problems.
We build some of the most amazing machines that you will ever see, and the software to run them. Never satisfied, we measure our performance in units that begin with pico or nano.
We believe we can always do better. We believe the winning idea can from anyone. We love what they do – not because it’s easy, but because it’s hard.
Students: Getting ready for real-world R&D and CS
Pushing technology further is teamwork, and our R&D and CS team is more than 7000 people strong, with major sites on three continents. Dozens of diverse, interdisciplinary teams work in parallel to meet a challenging development schedule.
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 your opportunity to get to know this world of industrial-strength R&D & CS and get a feel for 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?