AI-Driven Scientific Modeling Engineer

First Solar

Perrysburg (OH)

On-site

USD 80,700 - 135,000

Full time

14 days+

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Job summary

First Solar seeks a highly driven computational scientist or AI-augmented researcher to accelerate R&D decisions. The role blends physical reasoning, computation, data analysis and modern AI workflows to turn observations into engineering insights.

Responsibilities include developing models, software tools, and analytical workflows that transform experimental results into practical guidance for manufacturing and device engineering.

Qualifications

  • Bachelor's or higher with long experience in Engineering or Computational Science.
  • Ph.D. strongly preferred with 5+ years in relevant field including AI-enabled methods.
  • Experience applying computational, physical, statistical methods to challenges.

Responsibilities

  • Develop ML, AI and physics-informed models to explore structure–property–performance relationships.
  • Evaluate AI-assisted tools to improve modeling, data analysis and decision quality.
  • Translate hypotheses into scientific models and AI-enhanced workflows for R&D decisions.
  • Implement reusable computational tools with attention to robustness and reproducibility.
  • Identify uncertainties and high-value learning opportunities across programs.
  • Use experimental data for model calibration and validation.
  • Collaborate with multi-disciplinary teams to accelerate problem solving.

Skills

Machine learning
AI workflows
Scientific modeling
Data analysis
Scientific software
Model integration
Continuous learning
Ambiguity tolerance

Education

Ph.D. preferred
Bachelor's + 10 years
Master's + 8 years
Development Engineer II path

Tools

Python
Julia
C++
MATLAB
C#

Job description

First Solar seeks a highly driven computational scientist or AI-augmented researcher to accelerate R&D decisions. The role blends physical reasoning, computation, data analysis and modern AI workflows to turn observations into engineering insights.

Responsibilities include developing models, software tools, and analytical workflows that transform experimental results into practical guidance for manufacturing and device engineering.

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