# Combustion Development Engineer – Predictive CFD Simulation

**Company**: Audi Formula Racing GmbH
**Location**: Neuburg an der Donau
**Experience**: senior
**Job type**: Full-time
**Category**: Engineering
**Industry**: Motorsport

**Apply**: https://audi-formula-racing.jobs.personio.de/job/2698062?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_0c52c59c-dac

## Description

As a Development Engineer in the field of 3D CFD combustion at Audi Formula Racing GmbH in Neuburg (Germany), you are responsible for developing and optimizing the combustion process of the Audi Formula 1 power unit.

Your role involves leveraging state-of-the-art 3D CFD methodologies to develop predictive simulation approaches for designing future hardware and combustion process concepts, pushing the performance of the internal combustion engine to its physical limits under demanding conditions.

Key responsibilities include:

- Developing and optimizing combustion processes using high-resolution 3D CFD simulations

- Designing and analyzing thermodynamic aspects of gas exchange, mixture formation, ignition, combustion, and heat transfer

- Creating and applying predictive simulation methods for evaluating future combustion process and hardware concepts

- Planning, executing, and evaluating 3D CFD simulations, including interpreting results and deriving development measures

- Developing and validating models for direct injection, turbulent combustion, knock prediction, ignition, and heat transfer

- Correlating simulation results with single-cylinder and multicylinder test benches and component test rigs

- Optimizing combustion processes for sustainable and synthetic fuels

- Investigating fuel properties and their impact on mixture formation, ignition behavior, and efficiency

- Collaborating with fuel development partners to characterize and optimize future racing fuels

- Further developing simulation processes, toolchains, and automation solutions

- Utilizing modern HPC infrastructures for high-performance CFD simulations

- Applying data-driven methods for design space exploration, optimization, and model development

- Using data analytics, machine learning, and AI methods to improve simulation quality and development speed

The ideal candidate has:

- A Master's degree, Diploma, or PhD in Mechanical Engineering with a focus on Applied Thermodynamics, Automotive Engineering, Aerospace Engineering, Fluid Mechanics, or a comparable field

- Several years of professional experience in combustion development with a focus on 3D CFD simulation of high-performance combustion engines

- Profound understanding of fluid mechanics, thermodynamics, combustion processes, and mixture formation

- Experience with predictive simulation methods, spray, combustion, ignition, knock, and heat transfer modeling

- Familiarity with test bench and experimental data, as well as correlating CFD results with measurement data

- Experience in developing combustion concepts for sustainable or synthetic fuels

- Knowledge of modern sustainable racing fuels, eFuels, and advanced fuel characterization

- Experience with automated optimization processes, DOE methods, and surrogate models

- Passion for motorsport and high-performance powertrain technologies

- Experience in Formula 1, WEC, IndyCar, MotoGP, or comparable high-performance motorsport programs

- Excellent knowledge of at least one commercial CFD environment, such as STAR-CCM+, CONVERGE, or STAR-CD

- Linux skills and experience working with HPC cluster environments

- Programming and automation experience, preferably in Python

- Data analysis, statistical evaluation, and data-driven development methods

- Knowledge in the field of Machine Learning and AI applications for simulation and development processes

- CAD and geometry preparation skills

## Skills

### Required
- Mechanical Engineering
- Applied Thermodynamics
- Automotive Engineering
- Aerospace Engineering
- Fluid Mechanics
- 3D CFD simulation
- combustion development
- high-performance combustion engines
- thermodynamics
- combustion processes
- mixture formation
- predictive simulation methods
- spray modeling
- combustion modeling
- ignition modeling
- knock modeling
- heat transfer modeling
- test bench data
- experimental data
- CFD results correlation
- sustainable fuels
- synthetic fuels
- modern sustainable racing fuels
- eFuels
- advanced fuel characterization
- automated optimization processes
- DOE methods
- surrogate models
- motorsport
- high-performance powertrain technologies
- Formula 1
- WEC
- IndyCar
- MotoGP
- STAR-CCM+
- CONVERGE
- STAR-CD
- Linux
- HPC cluster environments
- Python
- data analysis
- statistical evaluation
- data-driven development methods
- Machine Learning
- AI applications
- CAD
- geometry preparation

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Source: [Apply at audi-formula-racing.jobs.personio.de](https://audi-formula-racing.jobs.personio.de/job/2698062?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)