PhD Opportunity: Financial Implications of Uncertainty in Cascading Climate Shocks.

Complex Systems Society; Leeds; On-site; GBP 15,000 - 20,000; Full time

Job summary

The Complex Systems Society offers a unique PhD opportunity in Leeds to explore the financial implications of cascading climate shocks. The successful candidate will develop a Python-based Agent-Based Model to simulate climate-related uncertainties and their impact on the financial system.

Co-supervised by Dr. Roger Cremades from the University of Leeds, this role requires a background in the financial sector and a keen interest in complexity science. Engage with leading researchers and contribute to methodologies that can enhance decision-making in climate-related challenges.

Qualifications

• Experience with Agent-Based Modeling and coding in Python.
• Understanding of complex systems science and financial modelling.
• Curiosity for tackling complexity and climate-related issues.

Responsibilities

• Develop an Agent-Based Model to simulate climate-related shocks.
• Review literature and identify necessary developments in existing models.
• Engage with experts and present findings related to cascading climate shocks.

Skills

Agent-Based Modeling

Python

Complex Systems Science

Financial Modelling

Education

Pre-doctoral experience in the financial sector

Job description

PhD Opportunity: Financial Implications of Uncertainty in Cascading Climate Shocks.

All available details can be found here: https://unrisk-cdt.ac.uk/. 

The key research question is: How can we move from traditional, static risk models and develop dynamic frameworks that capture uncertainty in cascading climate shocks?

The successful candidate will develop a novel Agent-Based Model (ABM) coded in Python to simulate how uncertainties from climate-related shocks cascade through the global financial system. You will explore the potential benefits of ABM beyond existing optimization paradigms in terms of incorporating uncertainty in cascading climate shocks. Your research will move beyond mapping cascades emerging from climate shocks and quantify the uncertainty they generate.

You will start by reviewing the literature and existing open-source models (see e.g. https://www.comses.net/codebases/?query=finance) to identify what further developments are required to integrate data e.g. on supply chains (e.g. FAOSTAT trade matrix) and climate vulnerability (e.g. AgMIP data). You will then explore the uncertainty in a cascading climate shock related to synchronous droughts.
The primary outcome will be a simulation tool that provides a new, dynamic representation of climate-financial uncertainty under cascading shocks. This will enable decision-makers to move from assessing single risks to stress-testing against complex, cascading scenarios currently impossible to model, supporting the design of robust strategies in the face of climate uncertainty.

The project will be co-supervised by Dr. Roger Cremades (main supervisor, University of Leeds) and Dr. Celian Colon (co-supervisor, Advancing Systems Analysis Program, IIASA), providing a unique combination of expertise in complex systems science, financial modelling and cascading climate shocks. The successful candidate will be enrolled and based at Leeds and is expected to engage with IIASA online and through short in-person visits, e.g. via programs like the YSSP and the SSSM.

Students with pre-doctoral experience in the financial sector and a curiosity for complexity science.

Other Information

https://environment.leeds.ac.uk/see/staff/13034/roger-cremades
https://eprints.lse.ac.uk/86505/1/Surminski_Using%20adaptive%20cycle_2018.pdf