Plans, designs and develops hardware, software, semiconductor or telecommunications systems.

* Developing physics-based models for Thermal/CFD/Chemistry applications for components in semiconductor capital equipment industry. Experience in commercial software like ANSYS Fluent, Star CCM+, or COMSOL, etc., is highly desirable.
* Data driven modeling - Juncture of physics-based modeling with data-driven, AI/ML methods:
* Developing methods for translating tool operational data into improved engineering designs
* Utilizing DOE, Optimization, and statistical methods to correlate Simulation data to experimental data.
* Stochastic optimization tools to bridge between simulation and experiments.
* Predict, measure, and analyze the experimental data of mechanical designs, process specification and software programs for semiconductor manufacturing equipment.
* Uncertainty Quantification & propagation, sensitivity analysis, statistical inference for model calibration, decision making under uncertainty.
* Multi-scale modeling from nano, meso to macro levels
* Provide design improvements of in-service tools based upon quantitative field measured failure data and less quantitative quality metrics as measured by Lam Research.
* Use advance statistical, probabilistic, and forecasting methods to best quantify design and performance of overall system.
* Provide written reports and oral presentation of results to design teams and management.
* Work directly with mechanical, electrical, process and software engineers to define design requirements, goals and objectives of design, CIP, testing and simulation plans.
* Leading and conducting design reviews in cross functional and matrixed environments.
* Strong written and oral communication. Self-starter to start own initiatives and projects for continuous improvement in capabilities and design.

• Preferred knowledge of chemistry, semiconductor metrology methods, and employing sensors and hardware designs in a vacuum environment is also a plus.
• Ability to work within a team to own and design concepts and drive design decisions.
• Established skills in building ML/DL/AI models using simulation data.
• Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc.) and deep learning.
• General understanding of uncertainty quantification, Bayesian optimization and probabilistic machine learning is required.

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.