Staff R&D Engineer — Lithography & Optimization

Synopsys Inc

Hillsboro (OR)

On-site

USD 160,000 - 210,000

Full time

12 days ago
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Job summary

Synopsys Inc. is seeking a highly skilled computational lithography modeling expert to advance Proteus-based optimization techniques. You will work across physics, mathematics, and software engineering to deliver robust models and fast calibration for leading-edge semiconductor processes.

The role requires deep numerical methods knowledge, strong C++ performance, and collaboration with field engineers and customers to validate solutions against real manufacturing data.

Qualifications

  • Strong background in physical modeling, statistics, and optimization.
  • Experience applying techniques to real-world problems.
  • Experience with non-linear systems and convergence analysis.

Responsibilities

  • Design and implement optimization techniques to reduce model calibration runtime.
  • Prototype mathematical models for lithography simulation in production-quality C++.
  • Calibrate and tune nonlinear model parameters using statistical analysis and heuristics.
  • Collaborate with cross-functional teams to integrate modeling solutions into workflows.
  • Analyze outlier data and develop sampling strategies to improve robustness.
  • Maintain and extend computational lithography models and diagnose performance issues.

Skills

C++
Python
Optimization methods
Numerical computation
Data analysis

Education

PhD in CS/EE/Physics/Applied Math
MS in related field + 5 years experience

Tools

Proteus

Job description

Synopsys Inc. is seeking a highly skilled computational lithography modeling expert to advance Proteus-based optimization techniques. You will work across physics, mathematics, and software engineering to deliver robust models and fast calibration for leading-edge semiconductor processes.

The role requires deep numerical methods knowledge, strong C++ performance, and collaboration with field engineers and customers to validate solutions against real manufacturing data.

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