Heat to Power Characterization Intern (Thermophotovoltaic/High-Temperature Systems)

Antora builds and deploys thermal batteries to power always-on industrial operations with low-cost energy. Factory-built in the United States, Antora’s modular thermal batteries deliver reliable heat and power, enabling industrial facilities of any size to decarbonize predictably and profitably. Antora is electrifying global industry while supporting U.S. manufacturing jobs, lowering costs for energy consumers, and enhancing the competitiveness of American industry.

We are growing our company with people who put team and mission first, value connection through laughter and joy, and build with humility and openness. We are committed to continue building a diverse, passionate, and creative team dedicated to a future where every industrial facility, everywhere on earth, is powered by abundant, clean, low-cost energy.

Position Summary

At Antora, we’re building the future of zero-emissions industrial energy, and that future depends on rigor, learning speed, and systems that scale. As a TPV Characterization Intern, you will work at the intersection of experimental hardware, data, and manufacturing systems to help Antora scale wafer production and accelerate progress toward automated defect detection. This role combines hands-on characterization, data-driven analysis, and systems thinking to directly support our mission to eliminate gigatons of industrial emissions. You’ll contribute to real production-scale challenges while gaining deep exposure to advanced energy hardware and manufacturing infrastructure.

Roles & Responsibilities

• Execute TPV wafer characterization (IV, EQE, optical measurements, etc.) and take ownership of routine data generation that supports rapid learning from reliability experiments.

• Quantify measurement variability and repeatability using univariate and multivariate analysis to establish statistically sound screening baselines for scaled production.

• Translate characterization data into defect-relevant signals by defining features, identifying correlations with performance or failure modes, and preparing clean, automation-ready datasets.

• Develop simple, interpretable rule-based indicators that support early-stage automated defect detection and localization.

Key Qualifications

• Currently pursuing a degree in Materials Science, Electrical Engineering, Mechanical Engineering, Physics, Chemical Engineering, or a closely related field.

• Strong experience working with databases, data analysis, and basic scripting (Python, MATLAB, or similar).

• Strong quantitative reasoning skills, including comfort working with statistics and correlated data.

• Comfort working hands-on with experimental hardware, laboratory tools, and measurement systems.

• Ability to organize, document, and communicate technical work clearly.

• Systems-oriented mindset with interest in manufacturing scale-up, automation, and infrastructure.

• Alignment with Antora’s mission, values, and team-first culture.

Additional Qualifications Desired

• Exposure to semiconductor, photovoltaic, or TPV device physics.

• Familiarity with multivariate analysis, anomaly detection, or introductory machine learning concepts..

• Prior internship or research experience in energy, climate, or advanced manufacturing systems.

Work Location: Onsite - San Jose, CA

Hourly Range: $35 USD - $45 USD

Please note that the hourly range listed for this position reflects Antora Energy's estimated pay rate. The actual rate offered will be determined based on a candidate's experience, year in school, and degree, as they relate to the position's requirements.

Additionally, this position does not offer visa sponsorship. Only candidates with current work authorization (e.g., F-1 visa with OPT/CPT authorization) will be considered.

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When it comes to stopping climate change, we need everyone. We believe that having a diversity of backgrounds and experiences strengthens all of us, and we strive to create an environment where every one of us is empowered to create meaningful change.