Research Engineer: Next-Gen Emissions And Aftertreatment Simulation

In this position...

This is an opportunity to work in a research environment defining the next generation of emissions and aftertreatment simulation. As diesel and gas powertrains evolve toward hybridization and electrification, the underlying simulation infrastructure must be reinvented to keep pace. In this role, you will research and build the simulation architectures needed to integrate models of fundamentally new system concepts - including hybridized gas/diesel emissions controls and electrified aftertreatment components such as electric DPFs and electrically heated catalysts - well before they exist in any production toolchain.

We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters. Ford's Research and Advanced Engineering team takes new ideas from theory to reality. Every day, we develop advanced energy management and propulsion technologies, create cutting-edge materials and manufacturing processes, and curate world-class cabin experiences that redefine what it means to drive a Ford.

What you'll do...

You will work alongside teams developing engine, combustion, aftertreatment, and controls models, with a focus on exploring how these models can be connected, represented, and evolved to support technologies that don't yet have established simulation methods. On a three to five year research horizon, you will also investigate how Agentic AI can be embedded directly into the simulation pipeline - to automate model calibration, accelerate integration, and fundamentally change the speed and quality of simulation.

This role is suited for someone who wants to operate at the leading edge of simulation research, prototyping new approaches and helping define the roadmap.

Research: Next-Generation Simulation Architecture:

• Research and prototype simulation architectures capable of integrating models for hybridized gas/diesel emissions control systems, enabling early-stage development and analysis of concepts ahead of production readiness.
• Develop and integrate models for electrified aftertreatment components - electric DPFs, electrically heated catalysts, and other emerging technologies - in close collaboration with hardware, combustion, and controls research teams.
• Explore new co-simulation and model-integration methods needed to combine models across teams, tools, and fidelity levels for these next-generation systems, where standard interfaces and workflows may not yet exist.
• Build proof-of-concept integration frameworks and demonstrate feasibility before handoff toward broader adoption.

Research: Agentic AI in the Simulation Pipeline:

• Investigate and prototype the application of Agentic AI within the simulation pipeline - for example, automated model calibration, intelligent scenario/test generation, self-diagnosing integration issues, or AI-assisted model reduction - on a 3-5 year roadmap.
• Evaluate emerging AI/ML and simulation tools and methodologies, assess their applicability to emissions and aftertreatment simulation, and build early demonstrations of value.
• Partner with technical leadership to help shape the long-term research roadmap for simulation of electrified and hybridized emissions systems.

Supporting Collaboration:

• Engage with teams building engine, emissions, and aftertreatment models (using GT-Power, WAVE-RT, and in-house tools) to understand existing modeling approaches and identify where next-generation architectures can build on or diverge from them.
• Document research findings, architectural concepts, and prototype results to inform future integration efforts.

What you'll do...

You will work alongside teams developing engine, combustion, aftertreatment, and controls models, with a focus on exploring how these models can be connected, represented, and evolved to support technologies that don't yet have established simulation methods. On a three to five year research horizon, you will also investigate how Agentic AI can be embedded directly into the simulation pipeline - to automate model calibration, accelerate integration, and fundamentally change the speed and quality of simulation.

This role is suited for someone who wants to operate at the leading edge of simulation research, prototyping new approaches and helping define the roadmap.

Research: Next-Generation Simulation Architecture:

• Research and prototype simulation architectures capable of integrating models for hybridized gas/diesel emissions control systems, enabling early-stage development and analysis of concepts ahead of production readiness.
• Develop and integrate models for electrified aftertreatment components - electric DPFs, electrically heated catalysts, and other emerging technologies - in close collaboration with hardware, combustion, and controls research teams.
• Explore new co-simulation and model-integration methods needed to combine models across teams, tools, and fidelity levels for these next-generation systems, where standard interfaces and workflows may not yet exist.
• Build proof-of-concept integration frameworks and demonstrate feasibility before handoff toward broader adoption.

Research: Agentic AI in the Simulation Pipeline:

• Investigate and prototype the application of Agentic AI within the simulation pipeline - for example, automated model calibration, intelligent scenario/test generation, self-diagnosing integration issues, or AI-assisted model reduction - on a 3-5 year roadmap.
• Evaluate emerging AI/ML and simulation tools and methodologies, assess their applicability to emissions and aftertreatment simulation, and build early demonstrations of value.
• Partner with technical leadership to help shape the long-term research roadmap for simulation of electrified and hybridized emissions systems.

Supporting Collaboration:

• Engage with teams building engine, emissions, and aftertreatment models (using GT-Power, WAVE-RT, and in-house tools) to understand existing modeling approaches and identify where next-generation architectures can build on or diverge from them.
• Document research findings, architectural concepts, and prototype results to inform future integration efforts.