The University of Leeds is inviting worldwide applications for a PhD investigating Greenland’s stability and future sea-level change. The project is part of the competitive UNRISK doctoral training programme. Its deadline is 13 January 2027. Applicants interested in computational climate research should consider both the scientific fit and the limited availability of international awards.
Research Focus
The research uses FAMOUS-ice to connect climate and ice-sheet simulation with evidence from past climates. It explores improved resolution, precipitation downscaling and uncertainty in Greenland’s future behaviour. Machine learning or process-based approaches may contribute to the modelling. The question offers a useful starting point for applicants who want to explain how evidence can strengthen, challenge or constrain a prediction.
Study Location and Academic Team
The university is in Leeds, United Kingdom. This is a computational study of Greenland rather than an advertised Greenland field placement. The School of Earth and Environment hosts the project. The opportunity belongs to UNRISK. Dr Lauren Gregoire and Dr Ruza Ivanovic are the named supervisors. Their research connects climate and ice-sheet change.
Applicant Background and Funding
The listed backgrounds include physics, mathematics, oceanography, meteorology, climate science and related environmental disciplines; programming or numerical modelling is highly desirable. UNRISK offers 15–18 awards across the programme, including full tuition, a UKRI-rate stipend, £6,000 individual research support and £5,000 cohort training per student. International awards are limited, and recipients must cover visa and Immigration Health Surcharge costs. Confirm your precise academic eligibility and the applicable stipend with the programme rather than assuming that a relevant subject automatically guarantees admission or funding.
Preparing to Discuss Model Evidence
One optional way to prepare is to construct a simple example of a model that matches one observation but fails another. Ask what you would conclude if adjusting a parameter improved one part of the comparison while making another part worse. Explain the difference between changing a parameter and changing an assumption in the model itself. This exercise is an illustration of research thinking, not an extra admissions test or a description of a task that the supervisors have assigned.
You could extend the example by identifying an observation that would be especially useful for distinguishing two competing explanations. State why that observation would help and what limitations it might still have. A thoughtful answer can acknowledge that evidence may narrow the possibilities without establishing a unique explanation. In an application, this kind of reasoning is more informative when connected to something you have actually studied or investigated than when presented as a collection of technical phrases.
Showing Your Computational Preparation
If the application requests a CV or supporting statement, choose a project that demonstrates how you worked with a quantitative problem from beginning to end. Describe the original question, the information available to you, the method you selected and how you checked the output. Make your contribution clear when the work involved collaborators, and avoid suggesting that every result from a team project was your own. A small but well-explained programming or modelling example can provide useful evidence without requiring you to claim expertise that you have not yet developed.
Where relevant, explain how you discovered an error, checked an unexpected result or made your work easier to reproduce. Distinguish a numerical result from the scientific conclusion you drew from it. If a method or programming language is new to you, identify it as a learning goal rather than listing it as an established strength. These suggestions concern the clarity of your evidence and should be adapted to the institution’s actual application questions and document limits.
Assessing Research and Financial Fit
Before choosing a doctoral project, write down which parts of the problem interest you most and which parts would require substantial new learning. Use that distinction to prepare focused questions rather than expecting an informal enquiry to assess your entire application. For financial planning, keep the scholarship’s academic support separate from personal expenses that you would need to meet yourself. Check the written award conditions before making commitments, especially where your ability to enrol depends on receiving a competitive international place.
How to Apply
Follow the current programme instructions for project selection and submission. Check the advertised title and academic contacts against your application fields before sending the form. Obtain any necessary clarification early enough to act on it before the stated deadline.
- View scholarship details and follow the linked programme application instructions.
- Identify the Greenland tipping-point project and check the current eligibility and supporting-document checklist.
- Submit through the specified route by 13 January 2027 and retain the confirmation.
Information Check
Information was checked on 23 October 2026. The announcement does not provide a numerical stipend rate. Reconfirm current terms before applying, and remember that an application or supervisor conversation is not an award offer.