Intern - AI‑Driven Process Development Deposition & Ion implantation
Core
Apply data analytics, machine learning, and statistical methods to accelerate thin-film deposition and ion implantation process development for advanced semiconductor technologies.
Role type
Intern, AI-Driven Process Development Engineer
Builds
Process optimization, variability control, and manufacturability for CVD, ALD, PVD metals and ion implant modules
Domain
Semiconductor manufacturing, thin-film deposition, ion implantation
Deliverable
production ML models
Required skills
Python (NumPy, Pandas, SciPy, scikit-learn), exploratory data analysis, machine learning (regression, classification, clustering, time-series), statistical modeling (regression, hypothesis testing, multivariate analysis, DOE), physics-informed feature engineering, anomaly and drift detection, data visualization, data pipeline development
Preferred skills
Semiconductor processing knowledge (CVD, ALD, PVD, metrology), DOE/SPC experience, cloud/big-data platforms (Azure, AWS, GCP, Spark), data visualization tools (Tableau, Power BI, Streamlit)
Technologies
Python, NumPy, Pandas, SciPy, scikit-learn, Azure, AWS, GCP, Spark, Tableau, Power BI, Streamlit
Responsibilities
Perform exploratory data analysis on large-scale process, tool, inline, metrology, and electrical datasets; Apply machine learning models to support process window optimization, variability reduction, and predictive learning; Develop physics-informed features relevant to CVD/ALD/PVD/ion implant processes; Conduct statistical analysis including regression, hypothesis testing, and DOE interpretation; Create visualizations and dashboards to communicate insights to process engineers and technical leadership; Collaborate with engineering and data science teams to scope intern projects and deliver reusable data pipelines
Seniority
Intern
