Early career postdoctoral researchers - Data Analyst – Behavioral Inference and Machine Learning for Global Water Systems
Centro Euro-Mediterraneo sui Cambiamenti Climatici
CMCC Foundation is a cross-cutting scientific research center on climate change and its interactions with the environment, society, the world of business, and policymakers. Our work aims to stimulate sustainable growth, protect the environment, and develop strategies for the adaptation and mitigation of climate change. CMCC's core objective is to conduct cutting-edge science, to train the next generation of scientists at both national and international levels, and to be a beacon for climate modelling.
The European Institute in Economics and the Environment (EIEE) is one of the three institutes of CMCC. It was established in 2018 in a trans-Atlantic partnership with Resources for the Future (RFF). It is one of the leading research centers on climate economics, featuring a diverse and international team of economists and natural scientists.
CMCC pursues fundamental and applied science with utmost scientific integrity, prioritizing data-driven science and providing data, information, and research results that can support informed public debate and decision-making processes. To achieve climate research objectives at the highest international standards, we invest in training all our talents, and strive to create a workplace where everyone can excel.
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Over the last decade, CMCC has experienced extraordinary growth. We are now embarking on a new chapter of our journey that will further boost CMCC’s global position in climate change research…Together!
Homepage: https://www.cmcc.it/
Earth and Space Science Informatics (ESSI)
Hydrological Sciences (HS)
We are seeking two highly motivated and talented early-career Postdoctoral Researchers with a strong background in environmental modelling, data science, or related fields to join the interdisciplinary team at the CMCC Foundation – Centro Euro-Mediterraneo sui Cambiamenti Climatici, based in Milan, Italy.
The successful candidates will contribute to the development and application of innovative data-driven approaches to understand and simulate human behaviour within global water systems.
The positions will focus on inferring behavioural patterns from large-scale observational datasets, with particular attention to reservoir operations, water abstraction practices, and the socio-economic drivers of sectoral water use. By applying advanced machine learning techniques, the researchers will reconstruct decision-making processes underlying water resource management and reveal the spatiotemporal dynamics of demand and infrastructure behaviour across global scales.
By integrating these behavioural insights into next-generation global hydrological and energy system models, the research will contribute to a more behaviourally realistic and climate-sensitive representation of water use and management — essential for planning resilient and sustainable futures.
These positions offer a unique opportunity to work at the intersection of artificial intelligence, hydro-climatic sciences, and environmental systems analysis, within a dynamic and international research environment. The candidates will play a key role in advancing scalable behavioural representations in Earth system models, fostering actionable insights for global sustainability challenges.
Through the integration of techniques such as feature extraction, explainable AI, clustering, transfer learning, and reinforcement learning, the researchers will extract behavioural insights from global-scale data on water use and infrastructure, reconstruct implicit decision rules governing water management, and assess their impacts under changing hydro-climatic and socio-economic conditions.