Structural/ Thermal Modeling Engineer III

Lam Research

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Tualatin, OR
Posted
150 days ago
Freshness
Confirmed live yesterday
Closes
Oct 11, 2026

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Similar $168k
$124k most similar roles pay here $202k

This listing doesn't post a salary. Most similar roles pay $140,300–$194,750.

Based on 240 similar postings.

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About Lam Research

Lam Research Corporation is a leading American supplier of wafer-fabrication equipment and services to the global semiconductor industry.

Lam Research currently has 299 open roles on FindRole.

Listed pay typically runs $114,000–$253,000 across 141 roles with salary data.

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At a glance

TL;DR · Structural/ Thermal Modeling Engineer III

Structural/ Thermal Modeling Engineer 3 joins the Global Products Group to develop physics-based models for Thermo-Elastic, Structural, and CFD applications within the semiconductor capital equipment industry. The role involves creating multi-scale models from nano to macro levels and integrating data-driven AI/ML methods with traditional physics to improve engineering designs. Key responsibilities include utilizing DOE, optimization, and statistical methods to correlate simulation data with experimental results, performing uncertainty quantification, and providing design improvements based on field failure data. Candidates must possess a PhD in Mechanical Engineering or a related field, focusing on solid mechanics, heat transfer, and fluid mechanics. Required skills include coding to supplement commercial software like ABAQUS, ANSYS, NASTRAN, or COMSOL. The work addresses complex technical challenges in semiconductor manufacturing equipment, specifically involving multi-physics modeling and material characterization in vacuum environments.

What you'll do

  • Develop physics-based models for thermo-elastic, structural, and CFD applications using commercial software like ABAQUS or ANSYS.
  • Integrate AI/ML methods with physics-based modeling to translate operational data into improved engineering designs.
  • Utilize DOE, optimization, and statistical methods to correlate simulation results with experimental data.
  • Perform uncertainty quantification, sensitivity analysis, and statistical inference for model calibration and decision making.
  • Develop and maintain live multi-physics models across nano, meso, and macro scales.
  • Provide design improvements for in-service tools based on quantitative field failure data and quality metrics.
  • Use advanced probabilistic and forecasting methods to quantify the performance of overall systems.
  • Deliver written reports and oral presentations regarding technical results to design teams and management.

What we're looking for

  • PhD in Mechanical Engineering or a closely related field.
  • Strong understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software.
  • Proficiency in coding to supplement commercial software for specific applications.
  • Experience with multi-physics, multi-scale, and data-driven modeling techniques.
  • Expertise in advanced statistical methods, DOE, optimization algorithms, and uncertainty quantification.
  • Ability to lead design reviews and collaborate within cross-functional, matrixed environments.
  • Strong written and oral communication skills for reporting results to teams and management.
  • Knowledge of semiconductor metrology, vacuum environments, or specialized numerical methods is preferred.

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