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Research Fellow in Climate Finance Analytics

Are you a researcher with demonstrable expertise in the analysis of climatological data and the implementation and interpretation of climate model projections? Do you have a demonstrable interest in engaging with stakeholders, particularly in public policy and the financial sector? Do you have a background within climate science? 

Successful candidates will report to Professor Jason Lowe in the School of Earth and Environment and Professor Iain Clacher, of Leeds University Business School, and will be part of the UK Centre for Greening Finance and Investment (CGFI). The researchers will contribute to the CGFI workstreams on generating and using data and analytics, and directly to the flagship on pensions and asset management.

Both candidates will focus on the evaluation of climate data and the tailoring of this data for use in financial analytics. One candidate will focus more on the understanding and evaluation of the physical credibility of the data as part of the Data and Analytics workstream. This will include tailoring and use of the data for financial analytics across all flagship areas of CGFI. The second candidate will focus more on the pensions and asset management flagship. Together the candidates will ensure appropriate climate data is used and that methods are fit for purpose.

The Data and Analytics workstream is the largest of CGFI and is the core engine of world-leading translational research and innovation within CGFI. The successful candidate will provide new understanding on selecting and applying appropriate climate science, analyses and modelling within financial decision making. Primarily this will draw on pre-existing climate model data and includes, for example, evaluating the performance of model simulations of extremes, assessment of robust across modelling approaches, scenario development and production of climate hazard and risk assessments suitable for helping financial institutions to manage physical-climate related risks and align their financing with resilience and adaptation goals. These goals include areas such as climate disclosure, risk management, stress testing and scenario analysis. While the other candidate will undertake the same activities but with a focus on the translation of these climate related risks for the pensions and asset management industry.

Both candidates will also work closely with collaborators across CGFI (particularly, Universities of Oxford, Imperial, Bristol, and Reading) to contribute to the development of cross-cutting underpinning methodological advancements, including new approaches to describing and characterising confidence levels, treatments of uncertainty in bringing together disparate data and models, approaches to characterising compounding and correlated risks, and tail-risk scenarios. The candidate will apply these to a range of hazards, which could include sea level, heat waves, drought, flood, and wildfire and will work as part of multi-disciplinary teams to connect science with decision-making approaches relevant to financial institutions.

Some experience of working with climate model data will be essential for the role and both researchers will work in one of the most cutting-edge areas in climate research with high societal impact. Qualified candidates must demonstrate a commitment to research excellence and impact in the relevant disciplinary field.

To explore the post further or for any queries you may have, please contact: 

Professor Jason Lowe 


Professor Iain Clacher

Tel: +44 (0) 113 343 6860, Email:

Location:  Leeds - Main Campus
Faculty/Service:  Faculty of Business / Environment
School/Institute:  Faculty of Business / Environment
Category:  Research
Grade:  Grade 7
Salary:  £35,333 to £42,155 p.a.
Working Time:  100% - We will consider job share / flexible working arrangements as well as hybrid/remote working
Post Type:  Full Time
Contract Type:  Fixed Term (1 role is for 30 months and 1 role until 31 March 2024 due to external funding)
Release Date:  Wednesday 26 October 2022
Closing Date:  Thursday 05 January 2023
Reference:  LUBEE1004
Downloads:  Candidate Brief  
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