Intern - AI-Driven Process Development (Deposition & Ion Implantation)

Job Title

Intern - AI-Driven Process Development (Deposition & Ion Implantation)

Role Summary

The intern will apply data analytics, machine learning, and statistical methods to accelerate thin-film deposition and ion implantation process development for advanced semiconductor technologies. The role sits at the intersection of process engineering and data science and supports CVD, ALD, PVD metals, and ion implant process teams.

Work includes extracting physics-aware insights from process, inline, metrology, and electrical data and translating findings into process knobs, experiments, and manufacturability recommendations.

Experience Level

Entry-level (Internship). No specific years of professional experience required; position is targeted at students currently enrolled in undergraduate or graduate programs.

Responsibilities

Core responsibilities focus on data-driven analysis, modeling, and communication to support process development.

• Perform exploratory data analysis (EDA) on large-scale process, tool, inline, metrology (XRR, XRD, CD, thickness, Rs), and electrical datasets to find trends and sensitivities.
• Apply machine learning models (regression, classification, clustering, time-series) for process window optimization, variability reduction, excursion detection, and predictive modeling of film properties and implant behavior.
• Develop physics-informed features (dose, pressure, temperature, power, gas flow, energy, tilt, etc.) relevant to CVD/ALD/PVD and ion implantation.
• Conduct statistical analysis including regression, hypothesis testing, multivariate analysis, and interpretation of DOE results.
• Implement anomaly and drift detection to identify tool-to-tool differences, chamber aging, and early signs of instability.
• Create visualizations, dashboards, and summaries to communicate insights and translate AI outputs into explainable narratives, feature importance, root-cause hypotheses, and process recommendations.
• Collaborate with process engineering, equipment, integration, and data science teams to scope intern projects and deliver complete project packages (code/notebooks, documentation, presentation-ready technical summary).
• Develop clean, reusable data pipelines for extraction, cleaning, and feature engineering.

Requirements

Must-have technical skills and capabilities are listed first; preferred skills are noted separately.

• Must-have: Strong Python proficiency for data analysis (NumPy, Pandas, SciPy, scikit-learn).
• Must-have: Solid understanding of statistics and data analysis fundamentals; experience with EDA and statistical modeling.
• Must-have: Familiarity with common ML approaches (regression, classification, clustering, time-series) and ability to apply them to real datasets.
• Must-have: Ability to create clear visualizations and communicate technical findings to engineers and leadership.
• Preferred: Coursework or experience in semiconductor processing (thin-film deposition: CVD, ALD, PVD; ion implantation; metrology and device fabrication).
• Preferred: Experience with data visualization tools (Tableau, Power BI, Streamlit) and/or cloud/big-data platforms (Azure, AWS, GCP, Spark).
• Preferred: Exposure to DOE, SPC, or manufacturing data analysis and experience with anomaly/drift detection in manufacturing contexts.

Education Requirements

Currently pursuing a Bachelor's, Master's, or PhD in Materials Science & Engineering; Electrical or Chemical Engineering; Physics; Data Science or Computer Science; Statistics, Applied Mathematics, or AI.

About the Company

Company: Micron Technology

Headquarters: Boise, Idaho, USA

Micron Technology is a global leader in memory and storage solutions, dedicated to transforming how the world uses information. The company offers a diverse portfolio of high-performance DRAM, NAND, and NOR memory products under the Micron and Crucial brands. With a commitment to customer focus and technological innovation, Micron drives advancements in artificial intelligence, 5G, and other data-centric applications, empowering users to learn, communicate, and progress.

Date Posted: 2026-05-14