PhD Studentship: The Viability of Machine-learning for Wind Loading and Wind Field Predictions

at University of Birmingham
Published February 18, 2023
Location Birmingham, United Kingdom
Category Machine Learning  
Job Type Scholarship  


The use of machine-learning (ML) techniques such as artificial neural networks to generate regression models of complex systems is expanding in a range of fields. There has been a recent increase in attempts to apply such models to wind engineering applications for structural loading and near-building wind field prediction, but these have been limited to relatively simple cases in which the ML models are trained and tested on the same data set, generated from the same building model and wind field conditions. Such work has limited application in prediction for the design of new structures.

This project will combine wind tunnel testing with ML model development to examine whether ML can generate truly predictive models for wind engineering applications. Wind tunnel tests will be used to quantify structural loading on a range of low-rise building models under different flow conditions, along with the local wind field. This data will be used to develop the ML models, which will then be used to predict loading on a subset of the models held back from the training data set.

During the course of this multi-disciplinary project you will develop practical skills in physical simulation, working closely with a team of world-leaders in the field, along with expertise in machine-learning and its application.

Please contact Dr Mike Jesson ( for informal enquiries about the project or applying.

Applications are welcomed from both engineering and numerical non-engineering disciplines (e.g. computer science, mathematics and physics). Applicants should hold (or be close to completing) an undergraduate degree at first class or high 2i level.


Jesson, M., Lombardo, F.T., Sterling, M., Baker, C., 2019. The physical simulation of a transient, downburst-like event – How complex does it need to be? JWEIA 189, 135–150. doi:10.1016/j.jweia.2019.03.021

Jesson, M., Sterling, M., Letchford, C., Baker, C., 2015a. Aerodynamic forces on the roofs of low-, mid- and high-rise buildings subject to transient winds. JWEIA 143, 42–49. doi:10.1016/j.jweia.2015.04.020

Jesson, M., Sterling, M., Letchford, C., Haines, M., 2015b. Aerodynamic forces on generic buildings subject to transient, downburst-type winds. JWEIA 137, 58–68. doi:10.1016/j.jweia.2014.12.003

Vita, G., Shu, Z., Jesson, M., Quinn, A., Hemida, H., Sterling, M., Baker, C., 2020. On the assessment of pedestrian distress in urban winds. Journal of Wind Engineering and Industrial Aerodynamics 203, 104200. doi:10.1016/j.jweia.2020.104200

Your Advert Reference

Dr Mike Jesson, Email:, Telephone: +441214143745

Funding Details

A Department of Civil Engineering scholarship, covering tuition fees and living costs, may be available to exceptional UK or overseas applicants who apply by 1st March 2023.