Research Associate in CFD and Aerodynamics Optimisation

University of Manchester; Manchester; On-site; GBP 45,000 - 60,000; Full time

Job summary

The University of Manchester is seeking a Research Associate to develop a CFD workflow for an industrial project with GB Cycling Team. You will design automated simulation pipelines, perform mesh generation, run CFD analyses and validate against wind-tunnel data to inform design and rider position optimisation.

You will collaborate with postgraduate and undergraduate researchers, contribute to turbulence modelling guidelines, and publish findings from a multi-disciplinary aerodynamics program in

Qualifications

• PhD or near completion in engineering, maths or physics with CFD/aerodynamics focus.
• Experience using CFD software such as OpenFOAM, Code_Saturne & Star CCM+.
• Experience developing scientific software using Python and/or C++.
• Experience with external aerodynamic simulations and mesh generation workflows.

Responsibilities

• Develop, validate and optimise high-fidelity CFD workflows for aerodynamic analysis of cycling equipment and rider configurations.
• Design automated simulation pipelines including geometry preparation, mesh generation, solver execution and post-processing.
• Validate CFD predictions against wind-tunnel measurements and establish best-practice guidelines for turbulence modelling and simulations.
• Support supervision of postgraduate and undergraduate researchers contributing to the project.

Skills

CFD workflow development

Python

C++

OpenFOAM experience

Code_Saturne

Star CCM+

Aerodynamic simulations

Education

PhD (or near completion) in engineering, maths or physics

Tools

OpenFOAM

Code_Saturne

STAR-CCM+

Job description

We seek a research associate to work on the development of a computational fluid dynamics (CFD) workflow in an industrially focused project in collaboration with Great Britain Cycling Team (GBCT).

The project focuses on the assessment of robust, accurate, and automated CFD methodologies for aerodynamic analysis of cycling performance, including workflow automation, mesh generation, simulation, post-processing and validation against wind-tunnel measurements. The resulting tool will subsequently be used to assist design and position optimisation activities.

You will be responsible for the following activities

• Develop, validate and optimise a high-fidelity CFD workflows for aerodynamic analysis of cycling equipment and rider configurations.
• Design automated simulation pipelines including geometry preparation, mesh generation, solver execution, and post-processing.
• Validate CFD predictions against experimental wind-tunnel measurements and establish best-practice guidelines for turbulence modelling and simulations.
• Support supervision of postgraduate and undergraduate research students contributing to the same project.

We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.

About You

We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:

Essential Criteria

• PhD (or near completion) in engineering, maths or physics, on research topics directly related to one or more of computational fluid dynamics, turbulent flows, aerodynamics, flow control.
• Experience using CFD software such as OpenFOAM, Code_Saturne & Star CCM+.
• Experience developing scientific software using Python and/or C++.
• Experience with external aerodynamic simulations.
• Experience with mesh generation and numerical simulation workflows.

Desirable Criteria

• Experience working in Linux and high-performance computing environments.
• Experience with turbulence modelling (RANS, LES, or hybrid RANS-LES methods).
• Experience working with industrial partners.
• Track record of peer-reviewed publications.
• Ability to contribute to future funding applications and external communications.

We value transferable skills and real-world experience as much as formal qualifications.

Our benefits include:

• Generous employer contribution pension
• 29 days annual leave plus bank holidays, along with Christmas closure
• Ride to work and EV car scheme available

For more information, please see University of Manchester Benefits. You can also find information on our Flexible and Hybrid working here.

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy.

Enquiries about the role, shortlisting and interviews

Name: Prof Alistair Revell

Email Address: [e-mail]

General enquiries and administrative support

[e-mail]

Technical and job portal support

https://jobseekersupport.jobtrain.co.uk/support/home

This role is not eligible for Skilled Worker visa sponsorship. Applicants must demonstrate the right to work in the UK.

Applications close at midnight on the closing date.

Further particulars (with person specification) linked below.