Publisher
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Andrei Shvarts

1 year ago

Environmental Science, Climate Change University of Glasgow, University of Edinburgh, Lancaster University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhDs

Deadline

Expired

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Country

United Kingdom

University

University Name
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Keywords

Computer Science
Environmental Science
Remote Sensing
Glaciology
Climate Science
Computational Science
Geophysics
Earth Science
Digital Twin Technology
Earth Observation
Cryosphere Science
High Performance Computing
Climate Dynamics
Gpu Computing
Supercomputing
Finite Element Analysis

About this position

???? One week remaining to apply for fully funded PhDs for September 2025 Entry via the ExaGEO DLA ??????????? https://www.exageo.org/

Exascale computing has the potential to transform how we tackle global environmental challenges by enabling the analysis of complex Earth system models. These models integrate atmospheric, hydrospheric, cryospheric, biospheric, and solid Earth processes while considering human influences such as economic and political decisions.

The ExaGEO DLA programme, supported by UKRI’s NERC: Natural Environment Research Council , trains PhD students in GPU-accelerated modelling and Earth observation data analysis. A collaboration between the University of Glasgow , the University of Edinburgh , and Lancaster University , ExaGEO focuses on addressing critical environmental issues through multidisciplinary research.

As climate change drives more extreme weather—stronger winds, severe precipitation, droughts, and rising temperatures—advanced predictive tools are essential. Researchers at the University of Glasgow are developing an Earth systems digital twin, leveraging exascale computing to simulate climate impacts at national and global scales.

Check out one of the proposed PhD projects focusing on a critical component of this broader effort - GPU-accelerated multiscale modelling for glacier sliding: https://lnkd.in/gx8d-eKB

This PhD project explores the glacier-bedrock interface, a key factor in predicting glacier sliding and its impact on freshwater availability, sea levels, and regional water resources. Using GPU-accelerated computing, you will develop high-resolution models that capture both microscale and macroscale interactions. The project employs MoFEM, an open-source finite element framework developed by MoFEM Community at the University of Glasgow , which is optimized for large-scale multiphysics problems and parallel computing. By integrating environmental and satellite data, you will calibrate and validate simulations to ensure real-world applicability. This research offers a unique opportunity to apply advanced computational techniques to pressing challenges in glaciology.

PhD PhDOpportunity ExascaleComputing ClimateChange EnvironmentalScience HPC FiniteElementAnalysis MoFEM GPUComputing EarthObservation Glaciology Cryosphere ClimateResearch DigitalTwin Supercomputing

Funding details

Fully funded PhDs

How to apply

Visit https://www.exageo.org/ for more information

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