Data-Driven Engineering Intern

7 days ago


Pittsburgh, Pennsylvania, United States EnerSys Full time

About Us

We are EnerSys, a global leader in stored energy solutions for industrial applications. Our mission is to provide innovative energy storage solutions that power the world's most demanding industries.

Job Overview

The Systems Modeling Intern will play a critical role in driving the development of next-generation battery systems. This intern will work closely with our team of engineers and energy storage experts to apply machine learning (ML) and artificial intelligence (AI) to analyze battery performance trends and improve State of Health (SoH) prediction.

Responsibilities

  • Support project delivery and contribute to the success of the Systems Engineering team
  • Develop and refine physical system models for mechanical, electrical, electrochemical, and thermal analysis
  • Collaborate with cross-functional teams to collect, analyze, and verify model data
  • Apply ML and AI techniques to identify trends in battery performance and enhance predictive analytics for SoH

Qualifications

  • Enrolled in a Bachelor's or Master's program in Electrical Engineering, Aerospace Engineering, Computer Science, Systems Engineering, or related fields
  • Proficiency in Python, R, MATLAB, or other programming languages
  • Familiarity with modular programming for scalable, reusable models
  • Possess a strong interest in data-driven engineering solutions and AI/ML techniques

What We Offer

  • Gain hands-on experience with industry-leading energy storage technologies
  • Contribute to real-world projects that make a difference in sustainable energy solutions
  • Develop technical and analytical skills that will set you apart in your career

EnerSys is committed to providing equal employment opportunities to all employees and applicants for employment, prohibiting discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.



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