Listening to La Soufrière: Fibre Optics and AI for the Next Generation of Volcano Monitoring (JOHNSON_UEA_ARIES27_CASE)
Key details
- Application Deadline
- 16 December 2026 23:59 UK Time
- Location
- UEA
- Funding Type
- Competition funded project (Students worldwide)
- Start Date
- 1 October 2027
- Mode of Study
- Full-time or Part time
- Programme Type
- PhD
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Project Description
Primary Supervisor - Dr Jessica Johnson
Scientific Background
A major challenge in volcanology is understanding and anticipating transitions in volcanic activity. Subtle changes within volcanic systems can precede hazardous eruptions, yet remain difficult to detect and interpret. This challenge is the focus of the NERC Large Grant Expecting the Unexpected (Ex-X): Understanding Dangerous Volcanic Transitions (dangerousvolcanoes.org). The 2020-21 eruption of La Soufrière, St Vincent, highlighted the importance of improved monitoring and hazard assessment. Recent advances in Distributed Acoustic Sensing (DAS) offer new opportunities for volcano monitoring by transforming fibre-optic telecommunications cables into dense seismic arrays.
As part of Ex-X, a DAS interrogator has been installed on a subsea fibre-optic cable around northern St Vincent. This provides a unique opportunity to investigate volcanic and tectonic processes in previously unmonitored areas. The enhanced spatial and temporal resolution afforded by DAS can reveal subtle seismic changes indicative of magmatic unrest that are usually missed by conventional networks.
Research Methodology
The candidate will develop automated workflows for processing continuous DAS data from St Vincent. Machine learning and signal-processing approaches will be used to detect, classify and characterise earthquakes. They will integrate DAS observations with the permanent seismic network operated by the University of the West Indies Seismic Research Centre (SRC) and a dense nodal deployment acquired through Ex-X. They will improve earthquake location calculations, apply ambient-noise imaging techniques to investigate subsurface structure, and evaluate how DAS can contribute to volcano monitoring. Particular emphasis will be placed on developing monitoring products that complement existing seismic networks, improve interpretation of unrest and support situational awareness.
Training
The candidate will receive training in seismology, volcanology, DAS, machine learning, scientific programming and geophysical imaging. They will gain experience in developing operational software for geohazard monitoring and working with large datasets. They will undertake fieldwork in St Vincent to maintain the DAS installation. Through a CASE partnership with SRC, they will spend several months embedded within an operational volcano observatory.
Person Specification
We seek an enthusiastic individual with a degree in geophysics or a related discipline. Experience of coding, data analysis or machine learning is desirable. An interest in geohazards and interdisciplinary research is essential.
Entry Requirements
At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5 overall, 6 in each category).
Funding
ARIES studentships are subject to UKRI terms and conditions(opens in a new window). Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance stipend (£21,805 p.a. for 2026/27) and a research training and support grant (RTSG). A limited number of studentships are available for international applicants, with the difference between 'home' and 'international' fees being waived by the registering university. Please note, however, that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK, such as visa costs or the health surcharge.
ARIES is committed to equality, diversity, widening participation and inclusion(opens in a new window) in all areas of its operation. We encourage applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Projects have been developed with consideration of a safe, inclusive and appropriate research and fieldwork environment. Academic qualifications are considered alongside non-academic experience, with equal weighting given to experience and potential.
After submitting their application for the relevant ARIES project(s), applicants are expected to complete the ARIES Equality and Diversity Form Applicants - 2027 Entry – Fill in form(opens in a new window).One form is required per application, so applicants applying to more than one project must complete a separate form for each.
Please visit www.aries-dtp.ac.uk(opens in a new window) for further information.
References
Robertson, R.E.A., Barclay, J., Joseph, E.P. & Sparks, R.S.J. (2023). An overview of the eruption of La Soufrière Volcano, St Vincent 2020-21. Geological Society, London, Special Publications, 539.
Jousset, P. et al. (2022). Fibre optic distributed acoustic sensing of volcanic events. Nature Communications, 13, 1753.
Mitchinson, S., Johnson, J.H., Milner, B. & Lines, J. (2024). Identifying earthquake swarms at Mt. Ruapehu, New Zealand: a machine learning approach. Frontiers in Earth Science, 12, 1343874.
Caudron, C. et al. (2024). Monitoring underwater volcano degassing using fiber-optic sensing. Scientific Reports, 14, 3128.
Lindsey, N.J. & Martin, E.R. (2021). Fiber-optic seismology. Annual Review of Earth and Planetary Sciences, 49, 309-336.