Research Assistant / Fellow in Earthquake Engineering – United Kingdom

[caption id="attachment_2547" align="alignnone" width="750"]Full-time Research Assistant : Fellow in Earthquake Engineering - University College London, United Kingdom Research Assistant : Fellow in Earthquake Engineering[/caption]

Applications are invited for Full-time Research Assistant / Fellow in Earthquake Engineering at The UCL Department of Civil, Environmental & Geomatic Engineering, United Kingdom.


The UCL Department of Civil, Environmental & Geomatic Engineering is a multidisciplinary department with a long tradition of excellence in teaching and research.

The Research Assistant / Fellow in Earthquake Engineering will play a leading role in the project TURNkey (‘Towards more Earthquake-resilient Urban Societies through a Multi-sensor-based Information System enabling Earthquake Forecasting, Early Warning and Rapid Response actions’), funded by the Horizon 2020 programme of the European Commission.

The post holder will contribute to the work package ‘Decision Support Systems (DSSs) for real-time (OEF and EEW) and near real-time (RRE) disaster prevention and risk communication’ together with providing close support to the planned testbed implications of the project’s developments and contributing to other aspects of this project where required, e.g. through reviewing deliverables.

Duration of the post is for 12 months in the first instance and will run from 1 February 2021 to 31 January 2022.


Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at research assistant Grade 6B (salary £31,542 – £33,257 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis.


The successful candidate will hold an MSc or PhD degree in Earthquake Engineering, Engineering Seismology or relevant subject area and have experience of Probabilistic Seismic Hazard Analysis (PSHA) and/or Performance-based Earthquake Engineering (PBEE).

Background knowledge of aftershock risk modelling is desirable. Knowledge of probability and statistics, Bayesian inference, and programming skills (such as Matlab or Python) are essential. A track record in publishing high-quality research would be an advantage.


If you have any queries regarding the application process, please contact Dr Carmine Galasso (


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