Worldwide, climate change is increasing the frequency and severity of extreme events such as floods and droughts, and is causing significant increases in socio-economic and human losses. To manage financial risks and reduce the economic losses caused by extreme events, risk hedging tools, such as index-based insurances, can play an important role for different stakeholders. These proactive tools, offer significant benefits particularly compared with the reliance on reactive post-disaster aid or the scale up of hard protection, investment-intensive infrastructure. However, if not appropriately structured, these tools can lead to unwanted consequences, as for example providing disincentives for risk reduction or may neither benefit the most vulnerable stakeholders nor foster climate resilience.The PhD research will develop novel financial risk-hedging tools to strengthen multi-sector resilience to climate change, mainly droughts and floods. In particular, the research activity will focus on:1) Designing optimal and robust insurances based on both the frequency and severity of insurance claims for hydro-meteorological risks. 2) Testing alternative Machine Learning techniques to optimally design a multivariate insurance index to pay out stakeholders, and estimate the probabilities of an extreme event happening at a target spatial resolution from forecasts and satellite data. 3) Evaluating the value of the insurance across multiple sectors using a multiobjective approach.

Qualifications for this position include an M.Sc. in Environmental Engineering or Economics or related fields. Profiles with a background in Artificial Intelligence, Applied Mathematics, Meteorology or Atmospheric/Climate Science will be also considered. Strong numerical and computational skills are required as well as English language skills both in oral and written communication.

The research will be carried out at the Department of Electronics, Information, and Bioenginering (DEIB), Politecnico di Milano. DEIB facilities several high-performance computing facilities on site and free access to national supercomputing cores, and scientific publications. A large warehouse of case studies, models and software tools for planning and management of water resources is available. The selected candidate will conduct research in the Environmental Intelligence Lab. EI-Lab’s mission is advancing environmental decision- analytics for supporting human decisions in complex engineering systems including multiple actors and exposed to evolving multisector demands and global change.