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12670 - Post-doc on remote sensing and machine learning

Remote: 
Full Remote
Contract: 
Freelance
Salary: 
35 - 35K yearly
Work from: 
Italy

Offer summary

Qualifications:

PhD in Environmental Sciences or equivalent., Proficiency in remote sensing data processing tools., Expertise in machine learning frameworks., Strong programming skills in Python or R..

Key responsabilities:

  • Develop and implement models for wildfire prediction.
  • Analyze large-scale geospatial datasets using advanced techniques.
CMCC Foundation logo
CMCC Foundation Research SME https://www.cmcc.it/
51 - 200 Employees
About CMCC Foundation
The Foundation Euro-Mediterranean Centre on Climate Change (CMCC) is a research centre on climate science and policy. The CMCC: - Integrates all studies on climate change and adaptation/mitigation policies - Promotes collaboration and synergy with international organisations, policy makers, and industry - Provides technical-scientific support to the institutions involved in the negotiation and international cooperation activities. CMCC produces thorough studies regarding climate variability, causes, and consequences, through the development of high-resolution simulations based on global models of Earth systems and regional models, with a particular focus on the Mediterranean area. CMCC's research assures the maintenance of highly reliable products and instruments, which are made available to the scientific community and to further studies on climate science and climate change impacts. CMCC maintains, checks, and develops numeric model simulations, which are used to study the effects of climate change on the following areas: economy, agriculture, coastal areas, marine and land environment, hydrogeological cycle, carbon cycle and human health.
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Job description

CMCC Position cod. 12670
Post-doc on remote sensing and machine learning applied to climate risk assessment
Deadline: February 28th, 2025



WHAT WE ARE LOOKING FOR

We are looking for a highly organized and motivated post-doc, specialist on remote sensing and machine learning applications for climate risk assessment, in particular related to wildfire prediction, and to growth, status and productivity of forests and their vulnerability to fires, to join our Impact on Agriculture, Forests and Ecosystem Services (IAFES) division, based in Sassari. The candidate should have a proven track record on international research and publication at the intersection of climate science, data analytics, and risk modeling.    



ABOUT US
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.


To learn more about this opportunity and submit your application, please refer to the following:


ROLE

The Post-Doctoral Researcher in this role will focus on advancing the use of remote sensing and machine learning to address critical challenges in climate risk assessment. Specifically, the role will center on wildfire prediction and the monitoring of forest growth, status, productivity, and vulnerability to fires. This interdisciplinary position combines expertise in geospatial data analysis, climate science, and artificial intelligence to deliver innovative solutions for understanding and mitigating the impacts of climate change on forest ecosystems.
The research conducted in this role will enhance the understanding of wildfire dynamics and forest vulnerability, providing critical insights for climate adaptation and mitigation strategies. Outputs will support the development of tools for early warning systems, sustainable forest management, and policy decision-making to build climate-resilient landscapes.
This position is ideal for a researcher passionate about leveraging advanced technology to address urgent environmental challenges and contribute to the sustainable management of forests under a changing climate.


RESPONSIBILITIES

The post-doc will support the IAFES division, with:
  • Wildfire Prediction:
    • Develop and implement machine learning models to predict wildfire occurrences and their potential impacts using remote sensing and environmental data.
    • Integrate climatic, meteorological, and vegetation datasets to identify risk factors and patterns associated with wildfires.
  • Forest Monitoring:
    • Use remote sensing data to monitor forest growth, health, and productivity across different ecosystems.
    • Develop algorithms to assess forest vulnerability to fire and other climate-related stressors.
  • Data Processing and Analysis:
    • Analyze large-scale geospatial datasets, including satellite imagery (e.g., Sentinel, Landsat, MODIS), LiDAR.
    • Employ advanced machine learning techniques (e.g., deep learning, random forests, ensemble models) to extract insights from diverse datasets.
  • Research Integration:
    • Collaborate with interdisciplinary teams to integrate findings into broader climate risk assessments and forest management strategies.
    • Communicate research outcomes through high-impact publications and presentations at conferences.

REQUIREMENTS
  • PhD in Environmental Sciences, Remote sensing, Agricultural and/or Forest engineering or equivalent subjects.
  • Proficiency in remote sensing data processing tools (e.g., Google Earth Engine, ENVI, QGIS).
  • Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Strong programming skills in Python, R, or similar languages.
  • Experience with geospatial analysis and visualization tools.
  • Very good knowledge of the English language, with strong communication skills for collaboration within a multidisciplinary team.
  • Availability to travel for limited periods


DURATION, COMPENSATION & BENEFITS
  • Please note that this opportunity will be issued both internally and externally.
  • The appointment period will be initially of 18 months, renewable for n°12 months additional months pending a positive evaluation. The gross annual salary range is from 28 to 35K Euros, depending on qualification and working experience.
  • Welfare package, for minimum 12 months contract.
  • Flexible working time as per internal policies
  • Support during the immigration process, if needed.

PROTECTED CATEGORY
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.
 

Applicants responding to this posting declare that they have read, understood and agreed to the “Official Rule for the CMCC Personnel recruitment".

We will keep your information on file for up to 1 year.

Required profile

Experience

Industry :
Research
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Hard Skills

Geospatial AnalysisData MiningRemote SensingMachine LearningClimate AnalysisEnovia (PLM Software)R (Programming Language)Google EarthForest ManagementEnvironmental Data AnalysisQuantitative AnalysisArcGIS (GIS Software)Python (Programming Language)PyTorch (Machine Learning Library)Data ProcessingTensorFlowScikit-Learn (Python Package)Wildfire Management

Other Skills

  • Collaboration
  • Communication
  • Problem Solving
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