Internship- Product Engineer Computational Model

Introduction

Are you interested in applying advanced modeling, data analysis, and semiconductor process knowledge to solve some of the industry's most complex manufacturing challenges? As a Product Engineer Computational Model Intern, you will contribute to innovative solutions that help enable the next generation of semiconductor devices.

Your assignment

The Product Engineer Computational Model Intern role supports ASML Brion's mission of advancing lithography-driven design and manufacturing solutions. Working at the intersection of product development and customer applications, you will participate in pattern coverage studies, computational lithography investigations, and technology evaluations that help improve modeling accuracy and product performance. This internship offers hands-on experience with advanced semiconductor technologies, data-driven problem solving, and industry-leading computational lithography solutions. The Product Engineer Computational Model intern will collaborate with engineers and domain experts while gaining exposure to real-world challenges in semiconductor manufacturing and process optimization.

• Conduct pattern coverage studies to support computational lithography modeling and product development.
• Analyze semiconductor manufacturing data to identify trends, opportunities, and process improvements.
• Support feasibility studies and technical evaluations for new product capabilities and customer requirements.
• Assist in developing best-practice approaches for standard and customized application solutions.
• Collaborate with product engineers and application teams to validate technical requirements.
• Utilize simulation and modeling tools to evaluate lithography and process performance.
• Document findings and present technical results to engineering stakeholders.

• Currently pursuing a master's degree or PhD in Electrical Engineering, Physics, Chemical Engineering, Semiconductor Manufacturing, Process Technology, or a related technical field.
• Experience through research, coursework, academic projects, or internships related to semiconductor technology, optics, modeling, or lithography.
• Familiarity with scientific computing, simulation tools, or data analysis techniques.
• Experience with programming or scripting languages such as Python, MATLAB, Perl, or similar technologies is preferred.
• Exposure to machine learning, optimization methods, or semiconductor process modeling is beneficial.