About the role
AI summarisedThis project-based internship within the New Technology Introduction (NTI) organization applies data analytics and AI modeling to wet etch and wet clean processes in advanced memory fabrication. The role involves using data-driven insights to identify process margins, understand failure modes, and accelerate technology learning.
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Key Responsibilities
- Develop and optimize data-driven and AI-based models for wet etch and wet clean processes.
- Identify process margins and potential failure modes during technology learning phases.
- Plan and execute Design of Experiments (DOE) to generate structured datasets.
- Analyze experimental data using critical dimension (CD) measurements, SEM, and other wet process characterization techniques.
- Evaluate model accuracy by correlating predictions with experimental outcomes.
- Explore process enhancement opportunities to meet defined structural and electrical criteria.
Requirements
- Currently pursuing a full-time undergraduate degree in Chemical Engineering, Materials Science and Engineering, Electrical Engineering, or Mechanical Engineering.
- Strong analytical and logical problem-solving ability.
- Basic knowledge or interest in data analytics, modeling, or machine learning techniques.
- Familiarity with experimental data analysis and interpretation.
- Clear written and verbal communication skills.
- Ability to manage multiple technical tasks within a structured project environment.