Data Science Internship: AI-Driven automation in Data Analysis

Data Science Internship: AI-Driven automation in Data Analysis

Introduction

Within D&E sector there is the DUV System Industrialisation Department which has the mission to accelerate the time to maturity in the manufacturing, servicing and upgrade deliverables; to drive the operational excellence by delivery of industrialized products and processes from D&E to Operations in line with their cost targets. The Cycle Time team is part of this Industrialzation department and works towards minimizing the time it takes to build and test the system in our factory, hence improving the execution efficiency and reducing costs.

Your assignment

As an intern you will be working with the Cycle Time team in D&E, responsible for monitoring, analyzing and reporting Cycle Time for New Product Introductions (NPI).

Your tasks will include:

• Develop an AI-powered solution to enhance decision-making process according to business challenges and user needs.

  • Translate business challenges and user needs into an ML research project
  • Understand the user needs and the available data to research on best suitable Machine Learning (ML) methods to accomplish the project goal
  • Develop ML models for detecting anomalies in system data that lead to performance issues

• Leverage ML techniques to uncover hidden patterns, generating new knowledge and enhancing the quality of insights.

  • Implement causation analysis to identify the root causes of performance issues. If the data is insufficient or the problem too complex, apply Explainable AI (XAI) techniques to explain and guide the users towards the likely root cause.
• Compare AI-driven insights with current automated methods to measure and assess the impact and the added value, including advantages and areas of opportunity

This is a bachelor/master graduation (thesis) or master apprentice (gain work experience) internship. The duration is 6-12 months for 3-5 days per week.

Your Profile

To be a perfect match for this internship, you:

• Have background in Data Science, Data Analytics, Software Technologies, Industrial Management (Focus of Data Analytics), Computer Science, or ICT;
• Have experience with data analytics, machine learning, AI, Data Visualization, process mining;
• Having knowledge of Python is required, SQL is a plus;
• Have analytical thinking, and problem-solving skills;
• Visual Communication;

Other requirements you need to meet

• You are enrolled at an educational institute for the entire duration 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 need to be located in the Netherlands to be perform your internship. In case you’re currently living/studying outside of the Netherlands, your CV/motivation letter includes the willingness to relocate.

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.

About Us

ASML is a leading supplier of lithography equipment, used by the world’s top chipmakers to print microchips that are increasingly powerful, fast and energy efficient. Working at ASML is inspiring, no matter what field you're in. That’s because we push the boundaries of technology: if it’s moving the world forward, chances are, we’re behind it. In fact, we’re probably a part of the electronic device you’re using right now.

We’re a global team of more than 32,000 people from 122 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.