Summer 2027 - Process Engineering Intern - DFBU Productivity - MS/PhD

Lam Research; Tualatin (OR); Hybrid; USD 30,000 - 47,000; Full time

Benefits offered by this job

Comprehensive benefits

Job summary

Lam Research Corporation’s DFBU Productivity group seeks MS/PhD interns to analyze dielectric deposition tools, run experiments in lab and clean-room settings, and present results to leadership by summer’s end.

You’ll work with mentors, applying data science and ML methods to predict productivity losses, building dashboards, and contributing to fleet productivity improvements while gaining exposure to hybrid work models.

Qualifications

• Must be an M.S. or Ph.D. student in Chemistry, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or Materials Science/Engineering with strong academic standing, returning to school after the internship
• Strong foundational understanding of physical sciences (Thermodynamics, Physical chemistry)
• Strong communication skills to convey project summary and results
• Ability to work in a clean-room environment wearing PPE, clean-room suit or smock
• Background in data science or AI/machine learning based process development
• Coursework or lab experience in thin films, CVD or plasma processing
• Experience with thin film analytical methods (e.g., SEM/TEM, XPS, XRD, ellipsometry)
• Familiarity with problem-solving methods such as SPC, DOE, 5-why or 8D
• Experience analyzing data with Python, JMP or MATLAB

Responsibilities

• Run experiments on dielectric deposition tools in lab and clean-room environments, and analyze film and metrology data
• Apply model-based and machine learning approaches to predict and prevent productivity losses
• Analyze tool and fleet data (uptime, downtime, chamber recovery) to identify top improvement opportunities
• Support root-cause investigations and preventive parts-replacement plans to reduce downtime and wafer scrap
• Present findings and recommendations to engineering and leadership in a short technical memo

Skills

Data analysis

Python

Machine learning

Communication

Clean-room work

Education

MS or PhD student in Chemistry/Physics/EE/Chemical/Mechanical/MSE

Tools

Python

MATLAB

JMP

SEM/TEM/XPS

Job description

The group you’ll be a part of

In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. Within it, the Dielectrics Deposition (DFBU) Productivity organization helps customers get the most from Lam’s deposition tools by raising capacity, reducing downtime and preventing wafer scrap.

The impact you’ll make

You will help improve the productivity of Lam’s Dielectric Films Deposition products in customer fabs, working with a mentor and experienced engineers to diagnose issues that limit tool throughput and uptime. By summer’s end you will own a defined project and present your results to DFBU leadership.

Example Summer Projects

Each intern owns one primary project matched to business needs and background; Ph.D. interns take on larger, more open-ended work. Typical projects include:

• Chamber recovery time reduction: A study of the steps between maintenance and return to production, with data-backed proposals to shorten recovery and the qualification wafer runs to support them.
• Preventive parts replacement: A ranked list of high-risk parts with recommended replacement intervals, built from field failure history and part-life data.
• Fleet productivity dashboard: An automated view of uptime, downtime drivers and chamber matching across a tool fleet, with a short guide for the engineering team.

What you’ll do

• Run experiments on dielectric deposition tools in lab and clean-room environments, and analyze film and metrology data
• Apply model-based and machine learning approaches to predict and prevent productivity losses
• Analyze tool and fleet data (uptime, downtime, chamber recovery) to identify top improvement opportunities
• Support root-cause investigations and preventive parts-replacement plans to reduce downtime and wafer scrap
• Present findings and recommendations to engineering and leadership in a short technical memo

Who we’re looking for

• Must be an M.S. or Ph.D. student (Masters or Doctorate) in Chemistry, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or Materials Science/Engineering with strong academic standing, returning to school after the internship
• Strong foundational understanding of physical sciences (Thermodynamics, Physical chemistry)
• Strong communication skills to convey project summary and results
• Ability to work in a clean-room environment wearing personal protective equipment, clean-room suit or smock

Preferred qualifications

• Background in data science or AI/machine learning based process development
• Coursework or lab experience in thin films, CVD or plasma processing
• Experience with thin film analytical methods (e.g., SEM/TEM, XPS, XRD, ellipsometry)
• Familiarity with problem-solving methods such as SPC, DOE, 5-why or 8D
• Experience analyzing data with Python, JMP or MATLAB

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.

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.