Job Description

Grade UE07: 40,497 to 48,149 per annum

CSE/School of Engineering

Full-time: 35 hours per week

Fixed term: 24 months

This Research Associate position will contribute to the BResilient project (Bamboo as a vital ingredient in reforestation strategies to promote resilient and sustainable communities and enterprises in Madagascar). The project is led by the Institute for Infrastructure and Environment at the University of Edinburgh, and in collaboration with colleagues at the School of GeoSciences, University of Edinburgh, ESSA, University of Antananarivo, Madagascar and Liverpool John Moores University.


The researcher will perform an analysis of available climate observations, including reanalysis data, to build a comprehensive characterisation of regional climate, including the occurrence of extremes (e.g., tropical cyclones) and their impact of regional resources (e.g., forests). By performing an analysis of future climate model projections, they will determine how the climate will evolve, and whether the frequency and severity of extreme events change with time. They will also estimate uncertainties, and the extent to which changes are anthropogenically driven as opposed to being part of natural fluctuations. The researcher will also make use of remote sensing data (e.g., vegetation and land-surface properties) to better constrain model-simulated climate. Use of machine learning methods (e.g., to improve model-based estimates or to provide further mechanistic insights into future climate projections) is strongly encouraged.


A full list of main responsibilities and the knowledge, skills and experience required for the role can be found in the full job description below. If you require any further information or wish to have an informal conversation about the role, please reach out to Thomas Reynolds ( T.Reynolds@ed.ac.uk ) and Massimo Bollasina ( Massimo.Bollasina@ed.ac.uk ).

Your skills and attributes for success:

Solid experience in the analysis of climate model data and observations (in situ, reanalysis, satellite-derived) Enthusiasm for climate research and independence to come-up with own ideas Willingness to develop and maintain international research collaborations with partners in academia and the humanitarian sector Track record of publishing results in international peer-reviewed journals Skills in machine learning and statistical analysis methods

Click

here

for a copy of the full job description.

Please apply including a cover letter and CV.

As a valued member of our team you can expect:

A competitive salary. An exciting, positive, creative, challenging and rewarding place to work. To be part of a diverse and vibrant international community. Comprehensive Staff Benefits, such as a generous holiday entitlement, competitive pension schemes, staff discounts, and family-friendly initiatives. Check out the full list on our

staff benefits page

(opens in a new tab) and use our reward calculator to discover the total value of your pay and benefits.

Championing equality, diversity and inclusion:

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.



Prior to any employment commencing with the University you will be required to evidence your right to work in the UK. Further information is available on our

right to work webpages

(opens new browser tab).


The University is able to sponsor the employment of international workers in this role. If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office's English Language requirements and apply for and secure a Skilled Worker Visa.

Key dates to note:

The closing date for applications is

21 May 2025.

Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browsers local time zone.