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Writer's pictureOmran Aburayya

Fully funded PhD position in Predictive Modelling at University of Exeter, UK

Predictive modeling

The University of Exeter’s Department of Mathematics is inviting applications for a PhD studentship fully-funded by the University of Exeter to commence on 23 September 2024 or as soon as possible thereafter.

 

Project Details


Predictive Modelling of Biomass Loss from Forests (Mathematics, Computer Science):

Forests play a key role in climate regulation, carbon sequestration, and biodiversity preservation. However, climate change threatens their resilience, causing increased tree mortality and biomass loss. This PhD project aims to understand and predict these changes using advanced remote sensing data, such as high-resolution biomass maps. The main challenge is to develop a robust model that can accurately identify tree mortality events and predict future trends using diverse data sources.

 

Funding and location

For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £19,237 for 4 years full-time, or pro rata for part-time study. The student would be based in the Centre for Doctoral Training in Environmental Intelligence and affiliated to the Department of Mathematics in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.

 

Entry requirements

Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. This project will require strong computational and mathematical skills, which the student should evidence in their application. 


If English is not your first language you will need to meet the required level as per the guidance at https://www.exeter.ac.uk/pg-research/apply/english/

 

Required documents

In the application process you will be asked to upload several documents:

  1. CV

  2. Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).

  3. Transcript(s) giving full details of subjects

  4. Two references from referees familiar with your academic work.

  5. English language proficiency

 

Application procedure

Applications are submitted online through (the online application portal).


• For full information, visit the official post webpage

Or

 

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