30+ days ago - req28278

Optics and Scatterometry Design Engineer

Research & development

Physics

In a nutshell

Location

Veldhoven, Netherlands

Team

Research & development

Experience

3-7 years

Degree

PhD

Job Category

Physics

Introduction

At ASML we use advanced mathematics and physics to keep fueling the semiconductor and electronic revolution. If your ambition is to apply your knowledge and skills to very complex challenges and you feel excited when those challenges lead to successful new products, please read further.
This position is open in the YieldStar Algorithms and Image Processing group, which is uniquely positioned between Research and product development and has the task to contribute to the creation of innovative concepts and products for ASML.

Job Mission

Within D&E, the group YieldStar Algorithms and Image Processing covers the development of physical, optical and mathematical models and methods required to infer the geometrical and physical parameters of the semiconductor process flow (such as overlay and scanner focus) from scatterometry-based metrology data. Relevant new metrics and algorithms, as well as new measurement functions, with optimal performance characteristics using the raw acquisitions are identified, designed and implemented. The group is also responsible for contributing to the invention of new ASML products providing state-of-the-art expertise in Scatterometry, Machine Learning, Image and Signal Processing.

Job Description

- Propose and develop scatterometry models, algorithms and calibrations which enable and improve semiconductor metrology solutions beyond the optical resolution limit
- Design and realize fully functional proof-of-concept subsystems on the edge of system specifications, costs and project planning, thereby contributing directly to products for customers world-wide
- Collaborate with the ASML Research department and on-product applications groups to actively contribute to the invention of new ASML products
- Contribute to the definition and execution of the Scatterometry Technical Competence roadmap
- Stay aware of the latest developments in your field of expertise
- Generate intellectual property protecting ASML products
- Communicate clearly the mathematical principles, algorithm solutions and physical models to the stakeholders

Education

Required: Ph.D. or equivalent level of education in Physics, or Applied Physics, or Electrical Engineering
Ideal candidate would have a solid experience in theoretical and numerical methods of diffractive micro/nanophotonics (light-matter interaction), and wave-based imaging principles in optical microscopes or other imaging systems
Postdoctoral and/or industrial experience in relevant fields would be an advantage

Experience

- Knowledge and experience in one or several following areas would be an advantage: electromagnetic simulations using RCWA, FDTD, FEM or other Maxwell solvers; physical modeling using Fourier and statistical optics, Jones and Mueller matrix calculus; design and implementation of algorithms for parameter estimation and inference; signal or image processing using machine/deep learning and neural networks; high performance computing
- Solid experience in Matlab coding is required. The candidate will be expected to develop new code, as well as to use and maintain parts of the existing code base

Personal skills

- Ability to explain complex physical models and algorithms in a crisp way, without omitting the essentials
- Drive creative solutions with the product and customer in mind
- Decisive and self-initiating in an ambiguous environment
- Ability to influence without power
- Team player
- Pragmatic approach and pro-active attitude, with result focus and a ‘can do’ spirit

Context of the position

This position is open in the YieldStar Algorithms and Image Processing group, which is uniquely positioned between Research and product development and has the task to contribute to the creation of innovative concepts and products for ASML.

Other information

Keywords: physical modeling, optical metrology, scatterometry, imaging, light-matter interaction, electromagnetic simulations, Fourier optics, statistical optics, computational imaging, machine learning, mathematical modeling, parameter inference, inverse problems, mathematical algorithms, numerical methods, high performance computing


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