About the Project
This fully funded PhD project is part of the QUARTILES Doctoral Landscape Award, a BBSRC and NERC-funded research and training programme designed to equip PhD students with the skills, expertise, outlook, and real-world experience needed to become the next generation of scientific leaders capable of addressing pressing environmental grand challenges such as climate change, biodiversity loss, and sustainability.
Mountains account for ~25% of the Earth’s total land area, ~32% of surface runoff, and support ~26% of the global population1. However, the complex terrain and rapidly changing climate make mountains increasingly prone to natural hazards such as hanging glacier (HG) collapse, causing ice-rock avalanches and associated flash floods2, affecting lives, livelihoods, infrastructure, and economy. Hazards involving HGs may include simultaneous occurrences and cascading effects, posing significant challenges in terms of modelling and prediction3. A recent example of such an event is in Switzerland, where a large portion of the glacier with ice rock and soil crashing down onto the alpine village of Blaten in the Lental Valley burying approximately 90% of the settlement. The distribution and prevalence of HGs is poorly perceived, and thus far no regionally-complete inventory of HGs is available. Therefore, this project aims to bring a transformative shift in the conceptualisation and modelling of high-mountain slope failures for possible mitigation. Detachment of HGs can be caused by climate change (leading to enhanced basal melting), as well as other geohazards (earthquakes/landslides/avalanches), and their occurrence often cascade to catastrophic debris flows, which are highly destructive due to large amounts of water and debris being released very quickly.
The workflow will be developed starting with data mining (glacio-hydrological/climatic/remote sensing), accompanied by developing manual or semi-automated approaches (multispectral/object-based) to map HGs using a variety of remotely-sensed (RS) datasets (e.g., Landsat/Sentinel 1/2/PlanetScope/ASTER), extendable to other glacierised regions. This will be followed by characterising HGs with highest hazard risk potential (based on proximity to habitation, size/volume, present and future thermal regime, proximity to glacial lakes and other HGs, slope/valley topography, sediments, vegetation presence, etc.). Finally, thermomechanical models will be run on the highest risk HGs to understand their hazard risk potential for generating cascading events with long runouts and massive volumes. The models will first be run under current climate using observational/reanalysis datasets and then under future climate scenarios taken from Coupled Model Intercomparison Project (CMIP6) models, driven by shared socioeconomic pathways (SSPs), and bias corrected and spatially downscaled to the scale of climate observations.
The candidate will undertake a training programme developing a suite of transferable skills in RS and glaciology. The project aims at meeting the UK’s international policy commitments under the United Nations Framework Convention on Climate Change. There have been significant investments in RS platforms over the past decade. Using these datasets for HG research is now timely, offers a high return on the large financial investment, and can also help understand the evolving thermal regime of Himalayan glaciers. Throughout the project, science communication will be undertaken.
Essential Skills/Experience: Proficiency in remote sensing and GIS
Desirable Skills/Experience: Programming skills in Matlab, Python, or R
Informal enquiries are encouraged! For further project information please contact the lead project supervisor by selecting the first listed name at the top of this advert and sending your enquiry.
———————————
ELIGIBILITY:
Promoting equality, diversity and inclusion is core to the QUARTILES Doctoral Landscape Award. We actively encourage applications from diverse career paths and backgrounds and across all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status, amongst other protected characteristics.
We also invite applications from those returning from a career break, industry or other roles. We typically require a minimum 2:1 in your first degree (or equivalent), but exceptions can be made where applicants can demonstrate excellence in alternative ways, including, but not limited to, performance in masters courses, professional placements, internships or employment – this will be considered on a case-by-case basis, and is dependent upon approval from the relevant host institution. We offer flexible study arrangements such as part-time study (minimum 50%), however this does depend on the nature of the project/research so will be considered on a case-by-case basis.
If you have any questions about your eligibility, please email us at quartiles-admissions@abdn.ac.uk
———————————
APPLICATION PROCEDURE:
- Please visit this page for full application information: How to Apply – QUARTILES DLA
- Please send your completed QUARTILES application form, along with academic transcripts and certificates to quartiles-admissions@abdn.ac.uk
- Please provide two academic references (we are unable to directly request references from your referees. If you would like to include references to support your application, please ensure they are provided directly to us. Some project supervisors may choose to contact your referees – please also include their contact details on your CV.
- Please ensure you submit all the required information and documentation.
- If you require any additional assistance in submitting your application or have any queries about the application process, please don’t hesitate to contact us at quartiles-admissions@abdn.ac.uk
Funding Notes
This 45 Month (NERC) opportunity is open to UK and International students (The proportion of international students appointed to the QUARTILES DLA is capped at 30% by UKRI).
QUARTILES studentships include a tax-free UKRI doctoral stipend (£19,795 for the 2025/26 academic year, the 2026/27 rate has yet to be released), plus a training grant of £9,000 to support data collection activities throughout the PhD.
QUARTILES does not provide funding to cover visa and associated healthcare surcharges for international students.
References
[1]Mt Res Dev2001,21(1),34-45
[2]Science2021,373,300–306
[3]Remote Sens2022,14(4),949
