Nicholas Stahl
Senior Lithography Process Engineer at Intel Corporation
Portland, Oregon, United States
Summary
👤
Senior🎓
Top SchoolNicholas Stahl is a Senior Lithography Process Engineer with 12+ years at Intel, combining a Ph.D. in chemistry with hands-on equipment, supplier, and high-volume manufacturing expertise. He leads end-to-end lithography development—from early layer learning and solvent selection to multipass patterning and process transfer—prioritizing defectivity control and zero excursions. Equally comfortable with a wrench or a codebase, he has implemented Python-based data analysis pipelines (pandas, Jupyter, matplotlib) to surface novel patterning insights and accelerate technology decisions. Nicholas drove the introduction of negative-tone patterning and tight-pitch multipass schemes into production, coordinating cross-functional and vendor partnerships to finalize process definitions across nodes. He is also a practiced mentor who has trained numerous engineers in robust development and sustaining operations. Based in Portland, Oregon, he blends deep organometallic and physical chemistry knowledge with pragmatic manufacturing instincts to deliver scalable, manufacturable lithography solutions.
12 years of coding experience
Bachelor of Science (BS), Chemistry, Bachelor of Science (BS), Chemistry at Drexel UniversityPh.D., Chemistry, Ph.D., Chemistry at Northwestern University
Spanish
Github Skills (25)
python10
data-science10
pandas10
data-structure10
data-structures10
data-analysis10
jupyter-notebook8
gtk8
jupyter8
qt7
matplotlib7
notebook7
data-visualization5
machine-learning5
conda4
Programming languages (3)
Github contributions (5)
stahlous/pandas
Oct 2015 - Oct 2015
Contributions:12 pushes in 12 days
manipulationmanipulation-librarydata-analysispythondata
stahlous/ml-coursera-python-assignments
Dec 2018 - Dec 2018
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
Contributions:1 push in 1 day
pythonandrew-nginstructionsmachine-learningcapability
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