Modeling Engineer 3

What you’ll do

• 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.
• Strong ability in closed-form solutions and analytical methods development and understanding fundamentals in fluid mechanics and heat transfer.
• Utilizing DOE, Optimization, and statistical methods and data driven modeling to correlate Simulation data to experimental data.
• Provide design improvements of in-service tools based upon quantitative field measured failure data and less quantitative quality metrics as measured by Lam Research.
• 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.
• Strong written and oral communication. Self-starter to start own initiatives and projects for continuous improvement in capabilities and design.
• Put your running shoes on: In this job you’ll work in a highly dynamic and rapidly changing environment within a team of interdisciplinary experts driving to solutions to the most challenging business needs.

Who we’re looking for

• • Minimum Master’s degree in Mechanical/Chemical Engineering with 10+ years of experience ; or a PhD with 5+ years experience; or equivalent experience in Computational Fluid Dynamics, Heat transfer, or related fields in a related industry, e.g., semiconductor, gas turbine, aerospace, automotive, etc.
  • Ability to work with a team to drive product development and design decisions. Propose design concepts and own decisions.
  • Strong ability and understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software. Building and maintaining codes of AI/ML models with either simulation or test data.  Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc.) and deep learning.
  • Coding ability to supplement commercial software for specific applications as needs arise.
  • Knowledge of chemistry, semiconductor metrology methods, and hardware designs in a vacuum environment is also a plus.
  • General understanding of uncertainty quantification, Bayesian optimization and probabilistic machine learning is required.

Preferred qualifications

Ability to effectively communicate and build relationships to interact, inform, influence, and communicate with key stakeholders at all levels across the company.

• Strong critical thinking skills demonstrated through problem-solving, attention to detail and innovation.
• Strong analytical skills demonstrated through First Principles Thinking, statistical Analysis and Physics-based Insights

Our commitment

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.