Internship: Bayesian Methods for System-level Qualification

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Statistical method | Internship: Bayesian methods for system-level qualification Beschrijving Introduction Within ASML, you will join a team focused on solving complex business challenges through data-driven insights and quantitative analysis. The team supports decision-making by transforming data into actionable recommendations that improve processes and performance. During this internship, you will contribute to the development and evaluation of advanced statistical and mathematical models that help address real business questions. You will work together with experienced professionals in an innovative and international environment while applying your academic knowledge to real-world challenges. This internship offers an excellent opportunity to develop your analytical skills and create meaningful impact. Your assignment In this internship, you will support the team in analyzing complex datasets and developing quantitative models to improve decision-making. You will investigate statistical relationships, evaluate model performance, and translate findings into practical recommendations. The core of this assignment is to develop a proof of concept for applying Bayesian statistics to system-level overlay qualification and determine whether the approach provides sufficient practical benefit for use in our daily engineering work. The internship provides an opportunity to apply advanced analytical techniques while working on business-relevant challenges. Your main responsibilities will be: - Familiarize yourself with overlay measurement data, performance metrics, machine populations, and current pre/post-change analysis practices; - Develop and validate a proof-of-concept Bayesian statistical model for system-level overlay qualification. - Evaluate the proposed approach using real measurement data, simulated data, or a combination of both; - Compare the proposed methodology with current methods and translate the results into cle...

统计方法 | 实习：用于系统级认证的贝叶斯方法 描述 简介 在ASML内部，你将加入一个专注于通过数据驱动洞察和定量分析解决复杂业务挑战的团队。该团队通过将数据转化为可操作的建议来支持决策，从而改进流程和绩效。在本次实习期间，你将参与开发和评估先进的统计与数学模型，以帮助解决实际业务问题。你将在一个创新且国际化的环境中与经验丰富的专业人士合作，同时将你的学术知识应用于现实挑战。本次实习为发展你的分析能力并创造有意义的影响提供了绝佳机会。 你的任务 在本次实习中，你将支持团队分析复杂数据集并开发定量模型以改进决策。你将研究统计关系、评估模型性能，并将发现转化为实用建议。本任务的核心是为将贝叶斯统计应用于系统级套刻认证开发概念验证，并确定该方法是否能为我们的日常工程工作提供足够的实际效益。本次实习提供了在应对业务相关挑战的同时应用先进分析技术的机会。 你的主要职责将是： - 熟悉套刻测量数据、性能指标、机器群体以及当前变更前/后分析实践； - 开发并验证用于系统级套刻认证的概念验证贝叶斯统计模型。 - 使用真实测量数据、模拟数据或两者结合来评估所提出的方法； - 将所提出的方法与当前方法进行比较，并将结果转化为清...

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