About the role
AI summarisedApply data analytics, machine learning, and statistical modeling to uncover actionable insights from large-scale semiconductor manufacturing and process datasets. Focus on identifying data patterns, detecting anomalies, building predictive models, and translating findings into clear recommendations that drive better decision-making across the semiconductor technology development lifecycle.
IDMOnsiteSTPG
Key Responsibilities
- Perform exploratory data analysis on large datasets to uncover patterns, trends, correlations, and anomalies relevant to semiconductor process and manufacturing data.
- Build and evaluate machine learning models (classification, regression, clustering, time-series) for predictive analytics and pattern discovery.
- Conduct statistical analysis including hypothesis testing, regression analysis, and A/B testing evaluation.
- Apply anomaly detection techniques to identify deviations and emerging trends in process, inline, and electrical datasets.
- Create visualizations and dashboards to communicate insights to technical and non-technical audiences.
- Develop data pipelines for data extraction, cleaning, and feature engineering.
- Collaborate with cross-functional teams including process engineering, manufacturing, and data science partners to scope projects and deliver actionable recommendations.
Requirements
- Currently pursuing Bachelor's, Master's, or PhD in Electrical Engineering, Materials Science, Physics, Data Science, Computer Science, Statistics, Mathematics, AI, or a related field.
- Available for a semester-long internship.
- Demonstrated proficiency in Python and SQL for data analysis.
- Ability to work independently with high self-motivation, time management, and prioritization skills.
- Must deliver a complete intern project package, including code/notebooks, documentation, and presentation-ready summaries.