About this role
The role
You will be part of an international collaborative project funded by a joint US and UK NSF-EPSRC proposal on “Predictive modelling for instability avoidance under human-structure interaction.” You will be based in the unique interdisciplinary and inclusive School of Engineering Mathematics and Technology.
What will you be doing?
The post-holder will be expected to carry out research using scientific machine learning to construct reduced-order models using the theory of invariant foliations. The methods will be developed in the context of data collected from microscopic models of individual agents, coupled to their environment. Together with the wider team, you will apply the method to simulate and analyse mathematical models of pedestrian bridges and similar civil engineering structures, together with crowd movement on the structure. You will be expected to take a leading role in preparing the results for publication.
You should apply if
Proficiency in creating, analysing and performing computation of mathematical models of physical processes Proficiency in creating and adapting scientific research software in an appropriate language. A track record in publication in appropriate venues. A PhD or equivalent experience in a topic of relevance to the project.
Additional information
For informal queries please contact:
Dr Robert Szalai, Associate Professor of Applied Mathematics +441174552372 [email protected]
or
Professor Alan Champneys, Associate Professor of Applied Non-Linear Mathematics +441174551041 [email protected]
To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:
https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/
Contract type: Open ended with fixed funding until 01/09/2028
Work pattern: Full time/35 hours per week
Grade: I/J – Pathway 2
Salary: £39,906 - £44,746 (Grade I) or £44,746 (Grade J) per annum depending on experience
School/Unit: School of Engineering Mathematics and Technology
This advert will close at 23:59 UK time on 13/09/2026
The interviews are anticipated to take place week commencing 28/09/26
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