CRSA: Postdoctoral research in development and testing of statistical models for forecasting (10285)

About UM6P:

Located at the heart of the future Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with international standards, is established to contribute to the development of Morocco and the African continent. Its vision is honed around research and innovation at the service of education and development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech.

About CRSA

CRSA is a transversal structure across several UM6P Programs. Research within the center is organized around several major areas that aim to ensure the challenging Food and Water security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and humans, with emphasis on sustainable management of natural resources (soil, land, water, agriculture) in the context of Climate Change. One of the center’s goals is to provide a set of services and operational products to users (local, national and international) that aid in the decision support of water and food systems.

Job Description:

We are seeking a highly motivated and skilled Postdoctoral Research Fellow to join our multidisciplinary research team on the project "Crop Growth Monitoring and Yield Forecasting". This project aims to revolutionize agriculture in Morocco by combining cutting-edge technologies, including crop growth models, remote sensing data, data assimilation, machine learning, and seasonal weather forecasts. As a Postdoctoral Research Fellow, you will play a crucial role in developing and testing statistical models for the accurate forecasting of precipitation and temperature over Morocco.

Key Responsibilities:

•  Statistical model development: Lead the development of advanced statistical models and machine learning algorithms for forecasting precipitation and temperature in Morocco. This will involve data analysis, model design, and algorithm implementation.
•  Work closely with the team to integrate various data sources, including historical weather data, remote sensing data, and crop growth data, into the modeling framework. Ensure data quality, consistency, and compatibility with the models.
•  Conduct rigorous testing and validation of the developed models. Compare model forecasts with actual weather conditions to assess accuracy and reliability. Continuously refine and improve the models based on validation results.
•  Collaborate with a diverse team of researchers, data scientists, agronomists, and remote sensing experts to ensure seamless integration of your models into the broader project framework.
•  Maintain comprehensive documentation of methodologies, code, and results. Contribute to the preparation of research papers, reports, and presentations to share findings with the scientific community and project stakeholders.

Experience and Qualifications:

• A Ph.D. in a relevant field, such as machine learning, climate science, environmental sciences, geoinformatics, or a related discipline.
• Proficiency in advanced learning techniques and statistical modeling.
• Strong programming skills in languages like Python or R.
• Professional experience in the application of Machine Learning algorithms in the mapping and correction of spatial data.
• Professional experience in data analysis, preprocessing, manipulation, and cleaning.
• Excellent communication and collaboration skills for interdisciplinary research.
• A track record of independent research and publica ons.
• Familiarity with climate data, remote sensing, and crop modeling is a plus.

How to apply:

Interested candidates are invited to submit a cover letter, curriculum vitae, a research statement, and contact information for three references. The cover letter should clearly articulate how the candidate’s skills and experience align with the requirements of the position and the goals of the project. 

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