Next-Gen Emissions Simulation Architect (Hybrid/Electrified)

Ford Motor Company; Dearborn (MI); Hybrid; USD 100,000 - 193,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

Parental leave

Vehicle discount program

Tuition assistance

Paid time off

Job summary

Ford Motor Company seeks a researcher to define next-generation emissions and aftertreatment simulation architectures. You will integrate models for hybridized gas/diesel controls and electrified components like electric DPFs and heated catalysts, shaping production toolchains years before deployment.

You'll explore Agentic AI for automated model calibration, smarter scenario generation, and robust integration.

Qualifications

• Master's degree required in mechanical/chemical/automotive engineering or related field.
• 3+ years of engine, emissions, or aftertreatment simulation experience.
• Experience developing or integrating physics-based models of combustion, emissions, or aftertreatment systems.

Responsibilities

• Research and prototype simulation architectures capable of integrating models for hybridized gas/diesel emissions control systems.
• Develop and integrate models for electrified aftertreatment components in collaboration with hardware and controls teams.
• Explore new co-simulation and model integration methods across teams, tools, and fidelity levels.
• Build proof-of-concept integration frameworks and demonstrate feasibility before handoff.

Skills

Python

MATLAB/Simulink

C/C++

Modeling & simulation

Research & prototyping

Education

Master’s degree in Mechanical / Chemical / Automotive Engineering or related field

Tools

GT-Power

WAVE-RT

FMI/FMU

Job description

Ford Motor Company seeks a researcher to define next-generation emissions and aftertreatment simulation architectures. You will integrate models for hybridized gas/diesel controls and electrified components like electric DPFs and heated catalysts, shaping production toolchains years before deployment.

You'll explore Agentic AI for automated model calibration, smarter scenario generation, and robust integration.