COMET Research Internships

To improve access to research in Geosciences, COMET offers paid research internships each summer.  The scheme is designed to give participating students the experience of undertaking scientific research and a flavour of what PhD-study is like.

Eligibility: The scheme is open to any undergraduate student currently in their 2nd/3rd or 4th year who has the right to work in the UK. We strongly encourage applicants from minority backgrounds, and from students who are the first generation in their family to attend University. Priority will be given to applicants from outside the host institution. Part of the work may be completed remotely in consultation with the supervisor.


Applications for the 2023 COMET Summer Internship programme are now closed.

We are offering three internships, based at the University of Leeds, the University of Bristol, and the University of Oxford.

The projects this year are:

Project 1: Exploring plume dynamics in the La Soufriére St Vincent eruptions of April 2021Supervisors: Dr Isabelle Taylor, Prof. Don Grainger, Prof. David Pyle (University of Oxford)

Project 2: What drove the 2020-2021 earthquake swarm at Casiri Volcano in Peru?
Supervisors: Dr Sam Wimpenny, Dr Lin Shen, Dr Camila Novoa-Lizama, Dr Tim Craig (University of Leeds)
Project 3: Synthetic Aperture Radar backscatter for monitoring on-going volcanic eruptions
Supervisors: Dr Edna Dualeh, Prof. Juliet Biggs (University of Bristol)


In summer 2022, COMET funded two students to undertake exciting six-week research internships:

Project 1 

Title: Improving Building Exposure Datasets using High-Res Imagery and Deep Learning
Supervisors: Dr. Scott Watson and Dr. John Elliott (University of Leeds)
Project aims: Maps of building distribution and characteristics are essential for assessing the risk posed to cities by earthquakes, volcanoes, floods, landslides and fires. Earth observation data are increasingly used to monitor urban sprawl, particularly high spatial-resolution satellite imagery. In this project, deep learning techniques were used to efficiently extract building outlines from satellite data over a target city (e.g. Kathmandu, Nairobi, Bishkek). The project plan was to investigate the accuracy of the deep-learning workflow for identifying buildings and augment the dataset with information derived from high-resolution digital elevation models to produce a comprehensive dataset of building stock to be used for risk analysis.
Key skills: (1) Using deep learning workflows with satellite imagery, (2) generating and analysing digital elevation models, (3) using geographic information systems.

Project 2

Title: Cosmogenic Isotope Analyses on Active Normal Faults
Supervisors: Dr. Laura Gregory, Prof. Andy Hooper, Dr. Sam Wimpenny (University of Leeds)
Project aims: Continental normal faults pose a significant hazard to populations across the globe. There is evidence that some normal faults experience variability in earthquake recurrence rates on thousand-year timescales. However, we do not know how variable these rates are in detail, and whether activity on one fault may influence another. For this project, the plan was to apply cosmogenic isotope analysis to determine how much faults in western Turkey and central Italy have slipped over the past 10,000 years. Cosmogenic isotopes accumulate within normal-fault surfaces as they are exposed at the surface in earthquakes, so the concentration of isotopes can be used to quantify the fault slip through time. Newly-developed tools were used to model the isotope data, and explore its implications for the earthquake cycle on normal faults.
Key skills: (1) using the geological record to interpret earthquakes, (2) careful laboratory work and data collection, (3) computer modelling and Bayes theory

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