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TEM Engineer at Applied Materials
Santa Clara, California, United States -
Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

TEM Analysis, Microstructure Analysis, Chemical Analysis, Electron Diffraction, EDS, EELS, Device Characterization, Machine Learning, Deep Learning, Python Programming, Creative Problem Solving, Semiconductor Knowledge, Crystallography, Diffraction, Collaboration, Communication

Industry

Semiconductor Manufacturing

Description
Perform daily TEM analysis, including microstructure and chemical analysis using electron diffraction, EDS, and EELS to support all BU process activities in AMAT. Develop/embrace groundbreaking solutions to device characterization at atomic resolution with high accuracy and reliability for the utilization in semiconductor process. Apply existing and newly developed technologies to tackle challenging process issues and support critical technology development projects. Correlate atomic scale structural and chemical information with processing, physical modeling, and device performance for faster cycles of learning. Drive technology roadmap through collaboration with instrument vendors, industry, and internal teams. Strong background and experience in materials characterization using TEM. Programming skills in machine learning (ML)/Deep learning (DL) and Python are required. A self-motivated, phenomenal teammate who enjoys working with others. Experience in creative problem solving and innovative solutions. Excellent knowledge in semiconductor, crystallography and diffraction. Positive and ambitious attitude with effective oral and written communications. Applicants should have a PhD degree or equivalent experience in Engineering, Physics, Materials Science or a semiconductor-related field.

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Responsibilities
Perform daily TEM analysis to support process activities in AMAT. Develop solutions for device characterization at atomic resolution and correlate structural and chemical information with device performance.