Document the workflow and present results at the end of the internship.
Who we’re looking for
Currently pursuing an MS or PhD in chemical engineering, physics, materials science, chemistry, or a related field.
Strong Python skills, including hands-on experience building and training models in PyTorch (or a similar framework such as JAX or TensorFlow).
Background in reaction kinetics, transport phenomena, or surface/plasma science.
Hands-on experience building machine-learning or regression models.
Strong analytical and communication skills, and the ability to work effectively in a team.
Note this is an onsite-flex position (3+ day in the office).
Preferred qualifications
Coursework or research in plasma physics or plasma-surface interactions.
Experience with surrogate modeling methods: Gaussian processes, neural networks, polynomial chaos, or reduced-order models.
Experience with GPyTorch/BoTorch, physics-informed neural networks, or uncertainty quantification.
Experience with design of experiments, sensitivity analysis, Bayesian calibration, or optimization.
Experience with physics-based simulation tools (finite element, Monte Carlo, or feature-scale/profile simulators).
Familiarity with semiconductor etch processes or SEM/TEM image analysis.
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.
Salary
CA San Francisco Bay Area Salary Range for this position: $29.75 - $48.25.
The above salary range for this position is relevant to applicants that reside or work onsite in the California, San Francisco Bay Area only. Salary offers will depend on factors that include the location you work from, your level, education, training, specific skills, years of experience and comparison to other employees already in this role. Actual salary may vary from salary offered due to numerous factors including but not limited to unpaid time off, unpaid leave, company mandated shutdown, and other relevant factors.
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.
