About the role#
This internship focuses on automating device characterization for perovskite panels. You will work alongside an engineer mentor to build data pipelines that standardize anomaly classification and improve panel screening. The role requires a six-month commitment, spanning either the Winter 2027 or Summer 2027 terms.
What you'll do#
- Build a Python pipeline to auto-extract Voc, Jsc, FF, PCE, Rs, and Rsh from raw J-V files.
- Classify anomalies including hysteresis, S-kink, shunting, and poor fill factor.
- Deliver an automated pass/fail report template.
- Extend the pipeline to assess YS300 EL images.
- Correlate image-derived metrics with reverse-scan IV metrics.
- Establish go/no-go screening criteria for panels entering the finishing stage.
- Present your project summary and accomplishments to the leadership team.
What you'll need#
- Current enrollment in a Bachelor's or Master's program in Physics, Electrical Engineering, Materials Science, or Data Science (junior, senior, or graduate level).
- Proficiency in Python for data analysis using pandas, numpy, and scipy.
- Understanding of PV device physics and common J-V curve anomalies.
- Knowledge of photoluminescence or electroluminescence for semiconductor characterization.
- Experience with image analysis, curve-fitting, anomaly detection, or basic machine learning.
- Strong documentation and communication skills.
Location & details#
- Location: Perrysburg, Ohio.
- Modality: On-site.
- Employment: Full-time, paid internship ($22-$25/hr).
- Sponsorship: Not available.
About First Solar
First Solar operates as a public company specializing in thin-film solar panel manufacturing and renewable energy. Founded in 1999, the firm maintains its headquarters in Tempe, Arizona. It employs approximately 6,715 people across its global operations. The company develops its solar technology through research and development labs located in California and Ohio.
How to get in at First Solar
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