Deadline: 12 February 2024 Midnight (GMT)
Interviews: 22 February 2024
Studentship Funding
The Sustainable Forest Transitions (SFT) Project is recruiting one full-time PhD student at the Global Development Institute (University of Manchester) from September 2024 to work on one of two themes:
Theme 1: Evaluating social and environmental outcomes of reforestation drivers using large-scale publicly available social and environmental datasets.
Theme 2: Development of rapid evidence synthesis methods and products using emerging artificial intelligence tools and other existing systematic review instruments. SFT seeks to advance a better understanding of the social and environmental outcomes of reforestation drivers globally. This position is fully-funded for 3.5 years, covering academic fees, an annual maintenance stipend of £18,622 (TBC for 2024-25) and research travel. You will be part of a multidisciplinary research team led by Dr Johan Oldekop, including post-doctoral researchers, PhD students, case-country partners (initially in Mexico, Brazil, India, Nepal and Indonesia), and other affiliated researchers.
Project Description
Scholars have devoted much attention to deforestation, yet processes driving the reverse phenomenon – reforestation – and their socioeconomic implications are poorly understood. SFT is conducting ground-breaking research to understand better how reforestation drivers (e.g., changes in migration, livelihoods or forest governance policies) affect forests and the communities that depend on them. SFT is a five-year, £1.7 million project selected by the European Research Council and funded through a UKRI Research Frontier grant hosted by the Global Development Institute. The project studies the changing nature of forest cover and human development at unprecedented scale and detail at global scales and in specific case-study countries, including Mexico, Brazil, India, Nepal and Indonesia.
Lead Supervisor
Dr Johan Oldekop
www.manchester.ac.uk/sftresearch/
PhD applicants can propose to focus on one of two themes linked to the SFT research agenda:
If proposing to work on Theme 1, you will analyse social and environmental outcomes of deforestation drivers. More specifically, you will help overcome existing conceptual, methodological and data limitations by combining secondary public socioeconomic (e.g., national census) and environmental data (satellite-derived forest data) with statistical approaches that increase the causal inference of analyses by emulating randomized experiments (quasi-experimental methods). The project has started to work in several countries (see above). Applicants may propose to work in any of these countries or propose to work in a different country or region.
If proposing to work on Theme 2, you will develop and test a rapid evidence synthesis methodology that leverages emerging state-of-the-art artificial intelligence tools already in the public domain (e.g., natural language processing tools such as ChatGPT and Elicit) as well as other existing systematic review instruments. You will develop new methodologies and data evidence products that specifically address one (or more) evidence gaps linked to forest restoration. You will lead the development of these approaches and establish new partnerships with evidence synthesis experts (e.g., the Collaboration for Environmental Evidence, Conservation Evidence, 3ie) evidence users (e.g., international donors and practitioners working in the space of reforestation/restoration and development) and key research networks working in the field of forests and livelihoods (e.g., the FLARE network).
Person specification
Excellence will be the primary selection criterion. Candidates must have strong quantitative skills and experience of handling and analysing datasets from diverse sources (e.g., remote sensing data, representative household surveys and/or systematic reviews and meta-analyses), acquired through relevant postgraduate training (e.g., in political or conservation science, economics, or geography).
Additional research training will be available to support further development and expertise in key analytical elements (e.g., econometrics, spatial statistics and/or remote sensing and meta-analyses).
If proposing to work on Theme 1, experience of working in one or more of the case countries and relevant language skills (e.g., Spanish, Portuguese, Hindi, Nepali, Bahasa) would be very beneficial but not essential.
Eligibility criteria
Academic:
In the majority of cases, eligible candidates will hold a Bachelor's (Honours) degree at 2:1 or above (or overseas equivalent) plus a Masters degree in a relevant subject with an overall average of 60% or above and a minimum mark of 60% in your dissertation (or overseas equivalent).
English language:
International applicants will need to provide one of the following:
• IELTS test minimum score - 7.0 overall, 7.0 in writing, 6.0 in other sections.
• TOEFL (internet based) test, minimum score - 100 overall, 25 in all sections.
• Pearson Test of English (PTE) UKVI/SELT or PTE
Academic minimum score - 76 overall, 76 in writing, 70 in other sections.
Further information
If you have any questions or would like to discuss this further, please contact Dr. Johan Oldekop
(johan.oldekop@manchester.ac.uk)
Residential eligibility:
This scholarship is open to international students.