Deadline: May 15th, 2025
The Division of Regional Models and geo-Hydrological Impacts (REMHI) at the Institute for Climate Resilience (ICR) is seeking an Expert in Data-Driven Approaches for Regional Climate Analysis to support the design, development, and deployment of AI for data-driven applications in regional climate research. The ideal candidate will have a strong background in the field of Regional Climate Model advanced statistical methods such as emulators and machine learning (ML), which are particularly relevant for high-resolution kilometre-scale downscaling. This role focuses on leveraging machine learning techniques to perform data-driven regional climate experiments and validation analysis at high spatial and temporal resolution. This role offers the opportunity to contribute to cutting-edge research and development projects, supporting the development and optimization of high-performance regional modeling frameworks for climate applications.
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.
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.
At CMCC you will find a strong, professional environment. Join an inclusive community that values diversity, where every voice is heard and respected. Help foster a culture of innovation and societal change, where individuals from all backgrounds can thrive and succeed.
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!
The Expert in Data-Driven Approaches for Regional Climate Analysis reports to the Head of the Regional Models and Geo-Hydrological Impacts (REMHI) division and is responsible for developing and applying AI algorithms for data-driven applications in regional climate research as emulators, which are particularly relevant for high-resolution kilometer-scale downscaling, and contributing to the advancement of hybrid modeling at the regional scale.
The Expert in Data-Driven Approaches for Regional Climate Analysis will support the REMHI division with:
The position has been opened within the project “Centro Nazionale Biodiversità (CNB Spoke Terra/Mare) - CUP Number: C83C22000550007.
The project promotes female and youth employment and the reduction of territorial gaps according to art. 47 “promotion of generational and gender equal opportunities for the awarding of public contracts for the implementation of the National Recovery and Resilience Plan (PNRR)”, of the Italian Law Decree no. 77/2021 converted into law no. 108 of 29 July 2021.
Belonging to legally protected categories (ex L. 68/99) will constitute a preferential condition.
Some fiscal benefits could be applied for repatriated workers or foreign researchers/professors, having the requirements defined by Dlgs 147/2015 (for repatriates) or Dl 78/2010 (for foreigners).
CMCC is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, familial status, and other legally protected characteristics. Please omit from your CV any data you or we might consider discriminatory.
This job announcement is an invitation to express interest in the above-mentioned CMCC Position.
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