About this role
Data Science | AI internship: Spatiotemporal forecasting methods Beschrijving Introduction The Applied Data Science team at ASML develops data-driven solutions that help improve the performance, reliability, and efficiency of advanced semiconductor manufacturing systems. You will work alongside experienced data scientists and collaborate with experts from different disciplines to translate complex challenges into impactful machine learning solutions. In this internship you will explore how advanced artificial intelligence methods can improve the prediction of overlay, a critical factor for semiconductor manufacturing quality and yield. This internship offers the opportunity to contribute to innovative research while gaining hands-on experience with state-of-the-art forecasting techniques. Your assignment In this internship, you will investigate advanced forecasting approaches that learn temporal patterns, spatial relationships, and interactions between variables directly from data. You will evaluate different modeling strategies and assess how design choices influence predictive performance. Working closely with specialists, you will build knowledge that supports future machine learning applications within ASML. Your main responsibilities will be: - Investigate spatiotemporal forecasting methods for overlay prediction - Develop and validate machine learning models using large-scale datasets - Build a prototype forecasting pipeline in Python - Compare advanced models with relevant baseline approaches - Analyze the impact of forecasting horizon, data selection, and model complexity - Document findings and translate results into actionable recommendations - Present outcomes to stakeholders within the research team This is a master's thesis internship for minimum 5 months, minimum 4 days per week (3 days on-site). The start date of this internship is as of February 2027, but an earlier start date is also possible . Your profil...