Solar PV Data Science Intern: Pipeline & Image Analytics

UEC; Perrysburg (OH); On-site; USD 30,000 - 34,000; Full time

Job summary

UEC is seeking an intern to build data pipelines that automate device characterization for perovskite solar panels. You will work with an engineer mentor using historical IV data, image/performance libraries, and computing resources.

You will develop a Python pipeline to auto-extract Voc, Jsc, FF, PCE, Rs, and Rsh from raw J-V files and classify anomalies, delivering the pipeline plus an automated pass/fail report.

Qualifications

• Pursuing a Bachelor's or Master's in physics, electrical engineering, materials science, or data science.
• Strong Python data-analysis skills (pandas, numpy, scipy, matplotlib).
• Familiarity with PV J-V characteristics and EL/PL is a plus.
• Experience with image analysis or basic ML is desirable.
• Excellent documentation and communication skills.

Responsibilities

• Build data pipelines to automate device characterization for perovskite panels.
• Collaborate with an engineer mentor using historical IV data, image libraries, and computing resources.
• Develop a Python pipeline to auto-extract Voc, Jsc, FF, PCE, Rs, and Rsh from raw J-V files and classify anomalies.
• Deliver the pipeline along with an automated pass/fail report template.
• Extend the pipeline to assess EL images and correlate image-derived metrics with IV metrics.
• Establish go/no-go screening criteria for panels entering finishing to standardize anomaly classification.
• Present accomplishments and project summary to leadership at internship end.

Skills

Python programming

Data analysis

Image analysis

Anomaly detection

Documentation & communication

Education

Bachelor's or Master's in Physics / Electrical Engineering / Materials Science / Data Science

Tools

Pandas

NumPy

SciPy

Matplotlib

Job description

UEC is seeking an intern to build data pipelines that automate device characterization for perovskite solar panels. You will work with an engineer mentor using historical IV data, image/performance libraries, and computing resources.

You will develop a Python pipeline to auto-extract Voc, Jsc, FF, PCE, Rs, and Rsh from raw J-V files and classify anomalies, delivering the pipeline plus an automated pass/fail report.