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.

• Position: Modeling Engineer(s)

• Location: San Jose, CA, Austin, TX, or Phoenix, AZ, USA

• Reports to: Head of R&D Center

• Job Responsibilities:

1. Develop physics-based models for Thermal, CFD, and Chemistry applications in semiconductor capital equipment using tools like ANSYS Fluent, Star CCM+, or COMSOL.

2. Integrate data-driven modeling with AI/ML methods to enhance simulation accuracy and improve design processes.

3. Translate operational data from semiconductor tools into actionable engineering improvements.

4. Apply Design of Experiments (DOE), optimization, and statistical methods to correlate simulation data with experimental results.

5. Use stochastic optimization to bridge the gap between simulations and real-world experiments.

6. Analyze and predict mechanical design performance and process specifications for semiconductor manufacturing equipment.

7. Perform uncertainty quantification, sensitivity analysis, and statistical inference for model calibration and decision-making under uncertainty.

8. Develop multi-scale models ranging from nano to macro levels for semiconductor applications.

9. Provide 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.

10. Collaborate with mechanical, electrical, process, and software engineers to define and refine design objectives, testing protocols, and simulation plans.

Qualifications:

1. PhD in Mechanical Engineering or a closely related field, with expertise in Computational Fluid Dynamics (CFD), Heat Transfer, or related disciplines.

2. Strong understanding of AI/ML concepts and hybrid physics-based AI/ML modeling.ㅁProficiency in coding and customizing commercial simulation software for specific applications.

3. Experience with machine learning tools (TensorFlow, PyPorch, Scikit-Learn) and deep learning models.

4. Knowledge of semiconductor processes, including PECVD, ALD, CVD, and experience working in vacuum environments is a plus.

5. Experience in uncertainty quantification, Bayesian optimization, and probabilistic machine learning.

6. Expertise in model-based design and industrial engineering for systems and equipment.

7. Strong programming skills (Matlab, Python, C, C++).

8. At least 3 years of work experience in semiconductor equipment design is preferred.

Benefits:

1. Competitive salary packageㅁHealth benefits

2. Relocation assistance

3. Apply Now: Send your resume to admin@tjlsolutionscorp.com