30+ days ago - req15685
Graduation assignment: Improving machine learning by inserting explicit domain knowledge
Computer science & software engineering
In a nutshell
No experience (Student)
Data science, Computer science & software engineering, Mathematics
Are you a Master student in Computer Science, Data Science or (applied) Mathematics with a broad interest and project experience in data mining and machine learning algorithms? Then this graduation project could be interesting for you.
Within ASML, CSI is the cross-sectoral improvement engine. We lead cross-sector projects with impact on availability, cycle time, costs and customer satisfaction by preventing and correcting known product failures, cross-platform and cross-part. To diagnose when a machine is about to break, or why a machine has broken down, a lot of domain knowledge and information gathered from sensors in the machine is needed. In this internship we want to investigate the value at the intersection of Knowledge Representation (KR) and Machine Learning (ML) in supporting this diagnosis.
Domain knowledge can be extracted from an expert or from documentation by using natural language processing techniques. The goal of this internship is researching how these approaches can be used to support diagnosis of machine failures. The internship will be executed within a specific use case in the CSI department. This will allow us to see the impact of incorporating knowledge driven techniques in order to improve accuracy of a machine learning algorithm. You will:
• Review literature and investigate possible formalization techniques in expressivity, ease-of-use and reasoning coming to arecommendation on suitable languages and formalisms to use;
• Actively contribute to a real use case, using these techniques to improve ML algorithm accuracy;
• Share results and progress on a regular basis, inspiring colleagues for new ways of working: incorporating expert or documented knowledge.
You are a Master student in Computer Science, Data Science or (applied) Mathematics. Broad interest and project experience in data mining and machine learning algorithms is a must. On top of this, affiliation with knowledge representation techniques such as Domain Specific Languages, Ontologies (e.g. OWL, RDF) is preferred. In addition, the English language is required, both in words as written.
This is a Master graduation assignment for 4-5 days a week with duration of minimum 6 months. The start date is in September 2020.
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 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
Pushing technology further is teamwork, and our R&D team is more than 5,500 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 and get a feel for that 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?