物理信息机器学习博士职位
PhD: Physics-Informed Machine Learning for Semiconductor Metrology
原帖优先:申请材料、截止时间与资格以原帖和学校官方说明为准。
AI 中文速览
- 研究内容
- 开发物理信息机器学习方法,用于半导体测量
- 申请条件
- 计算机科学、机器学习、人工智能、应用数学、物理或相关学科的MSc学位
- 待遇
- 每月€3115的工资和一系列的雇佣福利
- 申请方式
- 在线申请,截止日期为2027-02-24
- 材料清单
- MSc学位
- 机器学习或相关领域的背景
由 @cf/meta/llama-3.3-70b-instruct-fp8-fast 生成,博士岗判定置信度 90%。
结构化信息
- 截止
- (Europe/Amsterdam) 剩 140 天
- 学科
- 计算机科学
- 合同类型
- 雇佣合同
- 原文薪资
- EUR 3,115 / 月(税前)
- 税后月薪(估)
- ¥18,500;房租后 ¥10,600
- 估算假设
- 单身、无子女、雇佣合同的粗略估算,以学校 offer 为准;扣除率 25%;汇率日期 2026-10-01
- 原帖发布
- 本站收录
- 内容更新
- 来源
- AcademicTransfer(荷兰学术招聘) · 最近核对 2026-10-07
判定依据(原文摘录)
- is_phd
PhD program
- english_ok
proficiency in verbal and written English
- bachelor_ok
MSc degree
原文
Work Activities How can we combine machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these structures with extraordinary precision and do so quickly enough to keep up with large-scale production. This creates a fascinating computational challenge: how can we infer hidden physical properties from limited, noisy, and low-resolution measurement data?
In this project, you will develop a novel physics-informed machine learning approach that integrates physical simulations of the measurement process with its inverse reconstruction. A key challenge is the data-driven design of the experimental setup: exploring how the choice of measurements and configurations can be optimized to extract the most useful information for reliable parameter reconstruction.
You will work in close collaboration with the research department at ASML, the Centrum Wiskunde & Informatica (CWI, Prof. dr. Tristan van Leeuwen), and the AI4Science Lab, Informatics Institute, University of Amsterdam (dr. Patrick Forré), combining industrial relevance with academic depth in computational science and mathematical modeling.
Qualifications You have (or soon will have) a MSc degree in computer science, machine learning, artificial intelligence, applied mathematics, physics, or a related discipline, meeting the Dutch university requirements for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling with data-driven methods and are motivated to work at the interface of academia and industry. Strong analytical skills, a collaborative mindset, and proficiency in verbal and written English are essential.
Work environment ARCNL performs fundamental research, focusing on the physics and chemistry involved in current and future key technologies in nanolithography, primarily for the semiconductor industry. While the academic setting and research style are geared towards establishing scientific excellence, the topics in ARCNL’s research program are intimately connected with the interests of the industrial partner ASML. The institute is located at Amsterdam Science Park and currently employs about 100 persons of which 65 are ambitious (young) researchers from all over the globe. www.arcnl.nl
Working conditions The position is intended as full-time (40 hours / week, 12 months / year) appointment in the service of the Netherlands Foundation of Scientific Research Institutes (NWO-I) for the duration of four years, with a starting salary of gross € 3.115 per month and a range of employment benefits . After successful completion of the PhD research a PhD degree will be granted at a Dutch University. Several courses are offered, specially developed for PhD-students. ARCNL assists any new foreign PhD-student with housing and visa applications and compensates their transport costs and furnishing expenses.
More information? For further information about the position, please contact Lyuba Amitonova: l.amitonova@arcnl.nl and Maximilian Lipp (m.lipp@arcnl.nl).
Application You can respond to this vacancy online via the button below.
Online screening may be part of the selection.
Diversity code ARCNL is highly committed to an inclusive and diverse work environment: we want to develop talent and creativity by bringing together people from different backgrounds and cultures. We recruit and select on the basis of competencies and talents. We strongly encourage anyone with the right qualifications to apply for the vacancy, regardless of age, gender, origin, sexual orientation or physical ability.
Commercial activities in response to this ad are not appreciated.