Dielectric Deposition Process Intern: Optimize Uptime

Digitailor; Tualatin (OR); On-site; USD 28,000 - 39,000; Full time

Job summary

Lam Research in Oregon seeks a motivated MS/PhD student to join the Dielectrics Deposition Productivity group as a summer intern. You will work under mentorship on a defined project, run dielectric deposition experiments in a lab and clean-room, and apply data science techniques to improve tool uptime and throughput.

You will present results to the DFBU leadership and gain hands-on experience. The role emphasizes data analysis, modeling, and collaboration with experienced engineers.

Qualifications

• Must be an MS/PhD student in Chemistry, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or Materials Science/Engineering with strong academic standing.
• 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 and clean-room attire.

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 science

Python

Machine learning

Experimentation

Education

MS/PhD student in Chemistry/Physics/Engineering

Tools

JMP

MATLAB

SEM/TEM

XPS

Job description

Lam Research in Oregon seeks a motivated MS/PhD student to join the Dielectrics Deposition Productivity group as a summer intern. You will work under mentorship on a defined project, run dielectric deposition experiments in a lab and clean-room, and apply data science techniques to improve tool uptime and throughput.

You will present results to the DFBU leadership and gain hands-on experience. The role emphasizes data analysis, modeling, and collaboration with experienced engineers.