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Computer Science | Data Science internship: failure pattern analysis
Veldhoven, Netherlands
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- New graduates
- For current students
Are pursuing a master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Electrical Engineering, Systems & Control, or a related technical field
What you’ll work on
Full postingDevelop algorithms to clean, compress and structure noisy machine event data
Identify recurring failure signatures using data mining and machine learning
Build and evaluate supervised and unsupervised classification models
Validate findings using historical data and expert feedback
Compare failure patterns across machines and present results to engineers
From the employer’s posting
Develop algorithms to clean, compress, and structure noisy machine event data.
Identify recurring failure signatures using data mining and machine learning techniques.
Build and evaluate supervised and unsupervised classification models.
Validate findings using historical data and expert feedback.
Investigate similarities and differences between failure patterns across machines.
Education & alternatives
- Present results and recommendations to engineers and researchers. This is a master's thesis/non-thesis internship for a minimum of 6 months, 5 days per week (3 days on-site). The start date of this internship is as of February 2027 or earlier, depending on your availability.
To be suitable for the internship, you: - Are pursuing a master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Electrical Engineering, Systems & Control, or a related technical field. - Have experience with Python and machine learning techniques.
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 3, 2026today
- Recorded sightings
- 2
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
ASML Holding is hiring
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Scientist hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
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- Python
Where the posting names them
- Are pursuing a master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Electrical Engineering, Systems & Control, or a related technical field. - Have experience with Python and machine learning techniques. - Have knowledge of data analysis, classification methods, feature engineering, and model evaluation.
Your next step
Complete your application on asml.wd3.myworkdayjobs.com. The employer’s form will show what is required.
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Introduction
The Leveling department within Development and Engineering at ASML develops advanced wafer measurement solutions that support nanometer-level accuracy in semiconductor manufacturing. This internship focuses on improving the understanding of machine failures through data-driven analysis of event logs. You will help transform complex and noisy machine data into meaningful insights that support system reliability and performance. Your work will contribute to identifying recurring failure patterns and enabling more effective failure classification. This internship offers the opportunity to combine artificial intelligence, machine learning, and data mining in a highly innovative engineering environment.
Your assignment
During this internship, you will develop methods to analyze machine event logs and identify patterns related to machine failures. You will design and evaluate machine learning approaches that classify failure modes and uncover valuable insights from historical machine data. The results of your work may support engineers in understanding failure behaviour across multiple systems and improving future diagnostics.
Your main responsibilities will be:
- Develop algorithms to clean, compress, and structure noisy machine event data.
- Identify recurring failure signatures using data mining and machine learning techniques.
- Build and evaluate supervised and unsupervised classification models.
- Validate findings using historical data and expert feedback.
- Investigate similarities and differences between failure patterns across machines.
- Assess the practical value of the proposed solution for engineering use cases.
- Present results and recommendations to engineers and researchers.
This is a master's thesis/non-thesis internship for a minimum of 6 months, 5 days per week (3 days on-site).
The start date of this internship is as of February 2027 or earlier, depending on your availability.
Your profile
To be suitable for the internship, you:
- Are pursuing a master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Electrical Engineering, Systems & Control, or a related technical field.
- Have experience with Python and machine learning techniques.
- Have knowledge of data analysis, classification methods, feature engineering, and model evaluation.
- Are analytical and enjoy solving complex technical challenges using data.
- Are collaborative, proactive, and able to communicate technical findings clearly.
This internship is based in the Eindhoven region of the Netherlands. You will work closely with experienced engineers and researchers while contributing to meaningful challenges in the semiconductor industry. The assignment provides an opportunity to apply your academic knowledge to real-world engineering problems and gain hands-on experience in artificial intelligence, machine learning, and data-driven decision-making. If you are excited about turning complex data into actionable insights, we encourage you to apply for this internship.
Other requirements you need to meet:
- You are enrolled at an educational institute for the entire duration of the internship, and you are at least 18 years old at the start of the internship;
- 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);
- You attach your cover letter with a clear motivation on why you are interested in this internship assignment in particular;
- You need to be located in the Netherlands to be perform your internship. In case you are currently living/studying outside of the Netherlands, your application shows the willingness to relocate.
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.
Do you want to know more about the internship allowance, visa support and applying for an internship at ASML? Read this page.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Veldhoven, Netherlands
- Present results and recommendations to engineers and researchers. This is a master's thesis/non-thesis internship for a minimum of 6 months, 5 days per week (3 days on-site). The start date of this internship is as of February 2027 or earlier, depending on your availability.
- Work authorization
- You are enrolled at an educational institute for the entire duration of the internship, and you are at least 18 years old at the start of the internship; - 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); - You attach your cover letter with a clear motivation on why you are interested in this internship assignment in particular;
More source context
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. Do you want to know more about the internship allowance, visa support and applying for an internship at ASML? Read this page.