Listening to La Soufrière: Fibre Optics and AI for the Next Generation of Volcano Monitoring

Project Code: JOHNSON_UEA_ARIES27_CASE

Listening to La Soufrière: Fibre Optics and AI for the Next Generation of Volcano Monitoring

Project Code: JOHNSON_UEA_ARIES27_CASE

Project Description

Supervisors

Dr Jessica Johnson, School of Environmental Science, University of East Anglia – contact me

Dr Lidong Bie, School of Environmental Science, University of East Anglia

Dr Jacob Newman, School of Computing Sciences, University of East Anglia

Dr Corentin Caudron, Université Libre de Bruxelles

 

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.

Acceptable first degree subject(s): geophysics, geology, physics, environmental science, mathematics, computer science or a related discipline.

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.

Key Information

  • This studentship has been shortlisted for funding under the UKRI NERC DLA funding scheme and will commence on 1 October 2027. The closing date for applications is 23:59 on 16 December 2026.
  • 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 postgraduate researchers (PGRs) benefit from bespoke training and ARIES provides £2,500 to every student for access to external training, travel and conferences, on top of all Research Costs associated with the project. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses.
  • ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside non-academic experience, and our recruitment process considers potential with the same weighting as past experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis. International applicants should check whether there are any conditions of visa or immigration permission that preclude part-time study. All advertised project proposals have been developed with consideration of a safe, inclusive and appropriate research and fieldwork environment with respect to protected characteristics. If you have any concerns, please contact us.
  • For further information, please contact the supervisor. To apply for this Studentship, follow the instructions at the bottom of the page or click the 'apply now' link.
  • ARIES is required by our funders to collect Equality and Diversity Information from all of our applicants. The information you provide will be used solely for monitoring and statistical purposes; it will remain confidential and will be stored on the UEA SharePoint server. Data will not be shared with those involved in making decisions on the award of Studentships and will have no influence on the success of your application. It will only be shared outside of this group in an anonymised and aggregated form. You will be asked to complete the form by the University to which you apply.
  • ARIES studentships are subject to UKRI terms and conditions. Postgraduate Researchers are expected to live within reasonable distance of their host organisation for the duration of their studentship. Please see https://www.ukri.org/publications/terms-and-conditions-for-training-funding/ for more information.

Apply Now

Apply now via the University of East Anglia Application Portal