New College Grad System Engineer, Material Characterization (PhD - Santa Clara, CA)

Applied Materials•Santa Clara, CA

1d•Onsite

About The Position

Launch your professional engineering career at the forefront of semiconductor inspection technology. As a System Engineer, Material characterization, you will be responsible for developing original technical concepts for material discrimination in emerging product architectures and converting them into world best inspection and metrology products. You’ll join a supportive culture that encourages learning, experimentation, and professional growth.

Requirements

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, internship, personal projects, or research.
Analytical and methodical problem-solving approach.
Proficient in Python, MATLAB, or equivalent for data collection and analysis.
Excellent written and verbal communication skills.
Self-motivated; able to learn quickly in a fast-paced, multi-disciplinary team environment.

Nice To Haves

Internship or co-op experience in semiconductor equipment, instrumentation, or photonics.
Familiarity with optical systems, imaging, or laser-based instruments.
Experience with test automation or data acquisition systems.
Prior exposure to manufacturing, cleanroom, or lab operations.
Coursework or project experience in systems engineering.

Responsibilities

Survey and evaluate a wide range of optical and sensor‑based material‑characterization methods, such as fluorescence, hyperspectral, and polarization imaging, FTIR, SIMS/DART/DESI, LIBS.
Develop analytical and numerical models (e.g., physics theory, FDTD/RCWA, ray‑trace or wave‑optics simulations) to predict sensitivity, and discrimination capability.
Build and align benchtop optical setups, generate structured and clear experimental results.
Analyze data using Python and Matlab-based tools to compare experimental results with theoretical predictions. Leverage existing and emerging AI capabilities to maximize efficiency.
Create structured decision matrices ranking candidate approaches based on feasibility, performance, integration complexity, throughput constraints, hardware footprint, and risks.
Summarize and present to peers and management scientific & engineering recommendations identifying the most promising development pathways.
Generate detailed system requirements, proactively work with OE, ME, EE, SW & Algo cross-functional engineering teams to convert concept and bench results into functional prototypes and market leading products following best engineering practices.
Ability to act as a technical project manager, meeting performance, schedule, and cost targets.
Develop test plans and execute test procedures, calibration routines, and diagnostic protocols; document results with precision.
Support system-level troubleshooting and root cause analysis, design verification and validation activities across hardware, software, and algorithms.
Deliver necessary engineering documentation following defined Product Life Cycle process.
Develop and maintain IP portfolio and adhere to strict information security culture.