The University of Exeter is advertising a competitive PhD on uncertainty and spatial dependence in tropical forest forecasts. UK and international applicants may compete for funding. The deadline is 13 January 2027. Applicants should consider the research fit and financial conditions together before deciding whether to apply.
Research Focus
The project develops statistical and machine-learning methods for conservation planning. It examines uncertainty, spatial relationships and displacement effects. The intended work includes a decision-support tool for combinations of interventions. Read the project description as a starting point for identifying a question that interests you, rather than assuming that every possible method will appear in the eventual thesis.
Location and Academic Team
The university base is Exeter, United Kingdom. The research concerns tropical forest conservation. Economics hosts the advertised opportunity. It forms part of UNRISK. Dr Ben Balmford, Professor Daniel Williamson and Professor Ben Groom are named supervisors. The project links quantitative methods with conservation decisions.
Who Can Apply
Relevant quantitative backgrounds include statistics, mathematics, computer science, economics and related disciplines. Check the current programme requirements for the precise qualifications and supporting documents needed. A relevant subject or an eligible nationality does not by itself guarantee admission or an award.
Funding and International Conditions
UNRISK offers 15–18 awards across the programme, covering full tuition, a UKRI-rate stipend, £6,000 individual research support and £5,000 cohort training per student. International awards are limited, with visa and Immigration Health Surcharge expenses remaining personal costs. Confirm the applicable stipend and written award terms before making financial commitments.
Exploring the Research Problem
For optional preparation, imagine choosing between two possible interventions when the outcomes at several locations may be related. Explain what you would need to know before treating each location as an entirely separate decision. Consider whether a good result at one site would be enough to establish a benefit across the whole set of places you care about. This is a hypothetical research-thinking exercise, not a specified project case study, an assessment task or a claim about the eventual study region.
You could extend the example by asking what would have happened in the absence of an intervention. Write down the evidence that would help you assess that comparison and the assumptions that could not be checked directly. Separate an observed change from an explanation that attributes the change to one particular action. A clear discussion of those limits can show thoughtful interest in applied quantitative research without pretending that one model output proves the effectiveness of a conservation policy.
Presenting Evidence of Preparation
If you have completed a statistical or computational project, explain the question, the data, your individual contribution and the evidence used to assess the result. Describe how you handled a difficult assumption or a comparison that initially seemed misleading. If you worked with spatial information, explain what you actually did rather than listing a mapping package without context. If that experience is new to you, identify it as a learning goal and use another genuine quantitative example to demonstrate your current preparation.
If supporting materials are requested, make your individual contribution clear when discussing work completed with other people. Distinguish a class exercise, an unpublished report and a peer-reviewed research output instead of presenting them as equivalent achievements. Explain what your evidence can establish and what remained unresolved, including any limitation that would matter to the conclusion. Adapt these preparation suggestions to the actual application questions, since optional advice does not add requirements to the programme’s document checklist or guarantee a particular assessment outcome.
How to Apply
Use the current programme instructions to establish the submission route and complete supporting-document checklist. Review the exact project title and academic contacts wherever the form asks you to identify your research preference. An informal academic conversation can clarify fit, but it does not replace a formal application or constitute an admission or funding offer.
- View scholarship details and follow the linked institutional application instructions.
- Identify this named project and check the current academic and funding requirements.
- Submit through the specified route by 13 January 2027 and retain confirmation.
Before Submitting
Information was checked on 23 October 2026. Reconfirm the deadline and current terms before submission, particularly where your ability to enrol depends on receiving an international award. Keep a copy of the final form and any written clarification that materially affects your eligibility, financial expectations or decision to accept an offer.