Developing physics-based models for Thermal/CFD/Chemistry applications for components in ... Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc ...
Developing physics-based models for Thermal/CFD/Chemistry applications for components in ... Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc ...
Developing physics-based models for Thermal/CFD/Chemistry applications for components in ... Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc ...
Developing physics-based models for Thermal/CFD/Chemistry applications for components in ... Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc ...
OR · Hybrid
$54.50 - $72/hr
... as CFD, Electronic Design Automation, Graph Theory, Weather/Climate Modeling, and AI in HPC. You ... machine learning, or deep learning. * Experience in profiling and optimizing applications and ...
Machine Learning Cfd information
What are the key skills and qualifications needed to thrive as a Machine Learning CFD (Computational Fluid Dynamics) Engineer, and why are they important?
How does a Machine Learning CFD professional typically collaborate with domain experts and software engineers in a project setting?
What are Machine Learning CFD jobs?
What is the difference between Machine Learning CFD vs Data Scientist?
| Aspect | Machine Learning CFD | Data Scientist |
|---|---|---|
| Required Credentials | Degree in Engineering, Computer Science, or related fields; knowledge of CFD software | Degree in Statistics, Computer Science, or related fields; strong programming skills |
| Work Environment | Engineering firms, aerospace, automotive industries, research labs | Business, finance, tech companies, research institutions |
| Industry Usage | Simulation, fluid dynamics, engineering analysis | Data analysis, predictive modeling, business insights |
Machine Learning CFD focuses on applying machine learning techniques to computational fluid dynamics simulations, often within engineering contexts. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming skills and a strong analytical background, Machine Learning CFD emphasizes simulation and engineering applications, whereas Data Scientists focus on data-driven decision-making across diverse sectors.
Full-time
Posted 29 days ago
Lam Research rating
8.9
Based on 43 frontline employees who took The Breakroom Quiz
29th of 415 rated machine equipment manufacturers
Job description
In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry.
The impact you'll make
We move atoms that move the world.
At Lam Research, we create equipment that allows chipmakers to build device features more than 1,000 times smaller than a grain of sand. This tiny scale has a huge impact. Virtually every leading-edge chip inside the electronic products you use every day (TVs, smartphones, laptops, cars-even medical devices) has been made using our equipment.
As one of the world's most trusted suppliers in the semiconductor equipment industry, we're transforming technology. Our equipment places atoms so precisely that nearly every chip today is made using our innovations.
To build a prosperous career, start with an atom.
Should you choose to walk the path historically driven by Moore's law, your primary job function will involve cutting edge R&D activities in the Semiconductor Equipment Industry. If solving challenges no one has faced before or attempted are of interest to you, then Lam Research is the company for you.
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.
- Utilizing DOE, Optimization, and statistical methods and data driven modeling to correlate Simulation data to experimental data.
- Predict, measure, and analyze the experimental data for 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.
- 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
- PhD in Mechanical Engineering or closely related field with strong emphasis in Computational Fluid Dynamics, Heat transfer, Chemistry, or related fields with >6 years of experience 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.
IND123 #LI-NB1 #LI-Onsite
Our Perks and Benefits
At Lam, our people make amazing things possible. That's why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.
What Lam Research employees say
Pay
Benefits
Hours and flexibility
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About Lam Research
Sourced by ZipRecruiter
Lam Research designs and builds products for semiconductor manufacturing, including equipment for thin film deposition, plasma etch, photoresist strip, and wafer cleaning processes.
Industry
Manufacturing
Company size
10,000+ Employees
Headquarters location
Fremont, CA, US
Year founded
1980