Researcher, Energy & Propulsion Systems (Thermal Optimization)

General Motors • Full-time • United States • 2d ago

Job Description

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

The Role:

Energy and Propulsion Systems research is aimed at driving propulsion and vehicle efficiency, cost, and performance improvements. Research also focuses on advancing vehicle and propulsion systems to target enterprise cost reduction through warranty improvement and engineering development efficiency.

U.S. Person Status: This position is subject to export control regulations and requires the candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee, or refugee).

· Education:

Ph.D. in Mechanical Engineering, Thermal Sciences, Aerospace Engineering, Electrical or Controls Engineering, or a related discipline with demonstrated research experience, or
Master’s degree in a relevant field with ongoing Ph.D. studies.

· Experience: 0–3 years of relevant industry or research experience.

· Technical Expertise:

Strong foundation in heat transfer, fluid dynamics, refrigeration systems, and related engineering domains.
Knowledge of vehicle thermal loops, propulsion and vehicle thermal systems, and heat exchanger design principles.
Understanding of vehicle aerodynamics and its interaction with thermal systems.
Experience with design optimization workflows using CFD and CAE methods.
Proficient in CFD tools, such as StarCCM+, PowerFlow, Fluent.
Proficiency with 1D system modeling tools such as GT‑ISE, and familiarity with model reduction techniques.
Working knowledge of AI/ML frameworks and methods, including regression, classification, and deep learning.
Strong background in physics‑based modeling of continuous and discrete systems using first‑principles approaches.
Experience with multi‑disciplinary optimization (model‑based and data‑driven).

· Professional Skills:

Strong interpersonal skills with the ability to collaborate effectively across diverse teams.
Demonstrated ability to innovate and operate effectively in environments with ambiguity or evolving requirements.
Self‑motivated, proactive, and capable of driving independent work.

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Additional Information: This position may be eligible for relocation benefits.