PhD Opportunity
Ready to Rethink Ice Sheet Dynamics?
Ice sheets play a critical role in future climate scenarios, particularly through their contribution to sea level rise. However, the current mass balance of these ice sheets is highly uncertain, largely due to challenges in accurately modelling the complex interactions between ice dynamics, basal sliding, and the underlying topography. This PhD project aims to develop innovative mathematical and computational techniques to allow for improved model-based projections of ice sheet evolution, thereby enabling more reliable predictions of future sea level rise.
Project Description
During this PhD project the successful candidate will address several key challenges:
Estimation
Develop mathematically novel and computationally efficient methods to estimate both the basal sliding coefficient and the basal topography of the ice using high-fidelity Stokes-based ice flow models.
Uncertainty Quantification
Incorporate and rigorously quantify uncertainties arising from indirect, noisy, and sparse top-surface measurements, as well as other sources of uncertainty such as geothermal heat flux among many.
Modelling Innovations
Leverage recent theoretical and computational advancements that recast the complex ice flow problem—using shape optimisation methods—into a more tractable inverse problem. This approach builds on established techniques from previous work on related, but easier, estimation problems.
Broader Impact
Enhance the reliability of projections for ice sheet evolution in Antarctica, Greenland, and beyond, with potential applications in related fields such as microfluidics and tectonics.
Eligibility
The successful candidate will hold, or expect to complete soon, an Honours or Masters level qualification that includes advanced-level mathematics. We invite applications from motivated individuals with a strong background in applied mathematics, computational science, geosciences, engineering, or similar. Ideal candidates will have:
Computational PDEs
Experience in computational methods for partial differential equations.
Programming & Interdisciplinarity
Programming skills and a willingness to engage with interdisciplinary research.
Inverse Problems & UQ
Interest in inverse problems and uncertainty quantification.
Supervisory Team
Dr. Ruanui (Ru) Nicholson
University of Auckland
Dr. Oliver Maclaren
University of Auckland
Prof. Noemi Petra
University of California, Merced
What the scholarship includes
This support is provided through a Royal Society of New Zealand Te Apārangi Marsden Fund Fast-Start Grant.
Tuition Support
Full tuition fees for up to 3 years.
Annual Stipend
NZ$35,000 per year (tax-free) for a maximum of 3 years.
Travel Funding
Support for both domestic and international travel.
Collaborators
Learn More
Want more information about our PhD programme? Visit the University of Auckland webpage for full details on eligibility, application steps, and support available.
Apply Now
Ready to join us? Send your CV, cover letter, academic transcripts, and referee details to express your interest in this PhD opportunity.