PhD Studentship: Finding the Most Explosive Volcanoes on Earth

While advances in volcanology have revealed much about eruption processes, research has largely concentrated on a small set of well-monitored volcanoes, geographically skewed towards continental and northern hemisphere regions. This focus has left significant gaps in our understanding of many volcanoes, especially in resource-poor regions including island arcs in Southeast Asia. These areas coincide with the world’s highest volcanic activity, yet eruption histories, geological maps, and monitoring data are incomplete or absent. Volcanoes capable of very large magnitude eruptions (M ≥ 6), with the potential to cause severe regional or global impacts, remain missing from current risk assessments.

This PhD project will address this critical knowledge gap by identifying which volcanoes are most likely to produce highly explosive, large-magnitude eruptions. The student will combine global datasets with targeted field investigations to test the attributes hypothesised to favour such eruptions. Using a training dataset of well-studied volcanoes with known large eruptions, the project will employ statistical and machine learning (ML) methods to identify the strongest predictors of eruption magnitude. These predictive models will then be applied to poorly characterised volcanoes, producing a prioritised list for further research and monitoring.

Fieldwork in Southeast Asia, in collaboration with Indonesian partners, will test and refine these predictions. The student will also help organise a joint field course (with the Global Volcano Risk Alliance charity), to train local and international students in volcanic mapping, tephra sampling, dating techniques, and the analysis of volcanic ash for health impacts. This component will strengthen scientific capacity, foster community engagement, and produce valuable new data for the project.

By integrating advanced data science with traditional field volcanology and community-based training, the project will identify hidden high-risk volcanoes and contribute directly to monitoring priorities and the next generation of volcano scientists. The outcomes will be relevant to global disaster risk reduction efforts and will support targeted investment in monitoring infrastructure where it is most urgently needed.

Applicants should be comfortable working with quantitative analytical methods (specific machine learning skills can be developed during the PhD). Willingness for fieldwork in challenging environments is essential.

For further information on this project and details of how to apply to it, please click on the 'Apply' button above.

Further information on how to apply for a CENTA studentship can be found on the CENTA website: https://centa.ac.uk/apply/

Funding notes:

This project is offered through the CENTA3 DLA, funded by the Natural Environment Research Council (NERC). Funding covers: annual stipend, tuition fees (at home-fee level), Research Training Support Grant.

Academic requirements: at least a 2:1 at UK BSc level or a pass at UK MSc level or equivalent.

International students are eligible for studentships to a maximum of 30% of the cohort. Funding does not cover any additional costs relating to moving or residing in the UK. International applicants must fulfil the University of Birmingham’s international student entry requirements, including English language.  Further information: https://www.birmingham.ac.uk/postgraduate/pgt/requirements-pgt/international/index.aspx.

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