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Company Overview: Our client is a global leader in semiconductor equipment manufacturing, specializing in advanced deposition and heat treatment technologies for the semiconductor and display industries. They supply state-of-the-art equipment to leading semiconductor manufacturers worldwide. The company is committed to innovation, with over 60% of its workforce focused on research and development. They maintain a stable presence in both domestic and international markets, offering cutting-edge solutions for high-volume manufacturing.
ㅁPosition: Modeling Engineer(s)
ㅁLocation: San Jose, CA, Austin, TX, or Phoenix, AZ, USA
ㅁReports to: Head of R&D CenterJob Responsibilities:
ㅁDevelop physics-based models for Thermal, CFD, and Chemistry applications in semiconductor capital equipment using tools like ANSYS Fluent, Star CCM+, or COMSOL.
ㅁIntegrate data-driven modeling with AI/ML methods to enhance simulation accuracy and improve design processes.
ㅁTranslate operational data from semiconductor tools into actionable engineering improvements.
ㅁApply Design of Experiments (DOE), optimization, and statistical methods to correlate simulation data with experimental results.
ㅁUse stochastic optimization to bridge the gap between simulations and real-world experiments.
ㅁAnalyze and predict mechanical design performance and process specifications for semiconductor manufacturing equipment.
ㅁPerform uncertainty quantification, sensitivity analysis, and statistical inference for model calibration and decision-making under uncertainty.
ㅁDevelop multi-scale models ranging from nano to macro levels for semiconductor applications.
ㅁProvide design recommendations based on quantitative field failure data and other metrics.
ㅁUtilize advanced statistical, probabilistic, and forecasting techniques to assess system performance and design effectiveness.
ㅁCollaborate with mechanical, electrical, process, and software engineers to define and refine design objectives, testing protocols, and simulation plans.Qualifications:
ㅁPhD in Mechanical Engineering or a closely related field, with expertise in Computational Fluid Dynamics (CFD), Heat Transfer, or related disciplines.
ㅁStrong understanding of AI/ML concepts and hybrid physics-based AI/ML modeling.
ㅁProficiency in coding and customizing commercial simulation software for specific applications.
ㅁExperience with machine learning tools (TensorFlow, PyTorch, Scikit-Learn) and deep learning models.
ㅁKnowledge of semiconductor processes, including PECVD, ALD, CVD, and experience working in vacuum environments is a plus.
ㅁExperience in uncertainty quantification, Bayesian optimization, and probabilistic machine learning.
ㅁExpertise in model-based design and industrial engineering for systems and equipment.
ㅁStrong programming skills (Matlab, Python, C, C++).
ㅁAt least 3 years of work experience in semiconductor equipment design is preferred.Benefits:
ㅁCompetitive salary package
ㅁHealth benefits
ㅁRelocation assistance
ㅁApply Now: Send your resume to admin@tjlsolutionscorp.com