Research Assistant/Associate in computational fluid dynamics to study cloud

at  Imperial College London

FURTHER INFORMATION

We anticipate that this role will start on 1 July 2025. The successful candidate will be based in the Department of Civil and Environmental Engineering but will work across the Departments of Aeronautics and Physics.
Please refer to the job description for full details and essential requirements for the post.
This is a fixed term post for 2 years.
For informal enquiries about the post please contact Maarten van Reeuwijk on m.vanreeuwijk@imperial.ac.uk.
For queries regarding the recruitment process please contact Briony Webb on b.webb@imperial.ac.uk.
We are an equal opportunity employer and welcome applications from all backgrounds and disabilities. We will ensure that individuals with disabilities are provided reasonable adjustments to participate in the interview process and to perform crucial job functions, as well as other support including staff networks. Please contact us to request accommodation.

AVAILABLE DOCUMENTS

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Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.
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ABOUT THE ROLE

Applications are invited for a Research Assistant/Associate in computational fluid dynamics to study cloud-turbulence.
Rain formation is a critical part of the planetary energy balance yet the uncertainties in our ability to predict it are high. A large portion of this uncertainty is driven by the as-yet unknown interactions between high Reynolds number cloud-turbulence and liquid water droplets in clouds. This uncertainty can lead to a lack of accuracy in numerical weather prediction, driving uncertainty in future climate projections. Cloud adjustments in climate models are represented through changes to processes converting cloud water to rain, known as “auto-conversion”. Cloud droplets initially form via condensation of humid air; however, the formation of raindrops is accelerated by the turbulence-driven collision/coalescence process between these smaller droplets.
The objective of this project is to reduce uncertainty in parameterisations of auto-conversion and to assess newly developed auto-conversion parameterisations against historical and satellite data. Achieving this ambitious goal requires performance and analysis of high-fidelity simulations of droplet dynamics in highly turbulent flows.

WHAT YOU WOULD BE DOING

You will perform high-fidelity simulations of cloud-like turbulence in various set-ups with a focus on better understanding how turbulence and associated intermittency can impact droplet dynamics, and hence rain formation in clouds. Furthermore, you will contribute towards developing more accurate numerical weather prediction models based on your findings.