New College Grad System Engineer, Material Characterization

Applied Materials

Confirmed live today High trust
Closes in 2 days

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$138,000–$190,000 / yr
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live today
Closes
Oct 4, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $191k
This role $164k
$126k most similar roles pay here $249k

This role pays less than 67% of similar roles. Most pay $153,687–$227,500 — the shaded band above. At the midpoint, this role pays about $164k versus about $191k for comparable roles.

Based on 240 similar postings.

Employer

About Applied Materials

Applied Materials is the world''s largest supplier of equipment, services, and software for the semiconductor and display industries, enabling the production of chips and advanced displays. Industry: Semiconductor Equipment

Applied Materials currently has 179 open roles on FindRole.

Listed pay typically runs $131,000–$180,000 across 143 roles with salary data.

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View all roles at Applied Materials

At a glance

TL;DR · New College Grad System Engineer, Material Characterization

New College Grad System Engineer, Material Characterization (PhD - Santa Clara, CA) joins a team focused on semiconductor inspection technology to develop original technical concepts for material discrimination in emerging product architectures. The role involves surveying and evaluating optical and sensor-based characterization methods such as fluorescence, hyperspectral imaging, FTIR, SIMS/DART/DESI, and LIBS. You will build and align benchtop optical setups, develop analytical models using physics theory, FDTD/RCWA, or ray-trace simulations, and analyze data using Python and Matlab-based tools while leveraging AI capabilities. Responsibilities include creating decision matrices, generating system requirements, performing root cause analysis, and managing technical projects to convert concepts into functional prototypes. The work addresses the challenge of developing world-best inspection and metrology products for semiconductor manufacturing by integrating complex hardware, software, and algorithms within a rigorous product lifecycle.

What you'll do

  • Evaluate various optical and sensor-based material characterization methods like fluorescence, hyperspectral imaging, and FTIR.
  • Develop analytical and numerical models using physics theory and simulations to predict system sensitivity and discrimination capability.
  • Build and align benchtop optical setups to generate clear experimental results for product development.
  • Analyze data using Python and Matlab tools while leveraging AI capabilities to compare experiments with theoretical predictions.
  • Create decision matrices to rank candidate technologies based on feasibility, performance, integration complexity, and risk.
  • Generate detailed system requirements and collaborate with cross-functional teams to convert concepts into functional prototypes.
  • Execute test plans, calibration routines, and diagnostic protocols while documenting results for the product lifecycle.
  • Perform system-level troubleshooting and root cause analysis across hardware, software, and algorithms.

What we're looking for

  • PhD in Physics, Applied Physics, Electrical Engineering, Mechanical Engineering, Optical Engineering, Material Sciences, or a related field.
  • Strong academic background in physics, optics, or engineering fundamentals.
  • Strong theoretical understanding of material sciences and methods to characterize and discriminate different materials.
  • Hands-on lab experience through coursework, internships, personal projects, or research.
  • Proficiency in Python, MATLAB, or equivalent tools for data collection and analysis.
  • Excellent written and verbal communication skills.
  • Internship or co-op experience in semiconductor equipment, instrumentation, or photonics (preferred).
  • Familiarity with optical systems, imaging, laser-based instruments, test automation, or cleanroom operations (preferred).

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