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Postdoctoral Researcher in Coastal Ecosystem Monitoring Using Satellite Data

Employer
MOHAMMED VI POLYTECHNIC UNIVERSITY
Location
Morocco (MA)
Closing date
22 Jan 2025

Position Title: Postdoctoral Researcher – Coastal Ecosystem Monitoring and Agricultural Runoff Impacts
Duration: 2 Years
Location: Mohammed VI Polytechnic University (UM6P), Morocco

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.

Position Overview:
The Mohammed VI Polytechnic University (UM6P) is seeking a highly motivated Postdoctoral Researcher to work on an interdisciplinary project focused on monitoring the impacts of agricultural runoff on coastal ecosystems along the Moroccan coast. The project will utilize advanced satellite remote sensing data (e.g., Sentinel-3, Landsat, etc.) combined with additional open datasets to assess phytoplankton dynamics, nutrient loading, and harmful algal blooms (HABs). The research will contribute to understanding the ecological health of the region.

Key Responsibilities:

•    Conduct independent research focused on analyzing satellite-derived data (Sentinel-3, Landsat) to monitor coastal ecosystem changes.
•    Develop workflows in R, Python, or MATLAB to process and analyze ocean color data, with a focus on
chlorophyll-a, suspended particulate matter, and colored dissolved organic matter (CDOM).
 
•    Assess the impact of agricultural runoff on coastal water quality, particularly nutrient enrichment and
its relationship with phytoplankton blooms.
•    Use remote sensing to detect harmful algal blooms (HABs) and assess their spatiotemporal variability
along the Moroccan coastline.
•    Investigate links between satellite data and key ecological indicators, including the presence of phytoplankton species indicative of nutrient imbalances.
•    Collaborate with researchers and institutions (e.g., OCP Group) to align the research with sustainable
agriculture and environmental monitoring initiatives.
•    Contribute to scientific publications, project reports, and presentations at international conferences.
•    Potentially assist in proposal writing to seek additional funding for fieldwork.

Qualifications:

•    PhD in Oceanography, Environmental Sciences, Remote Sensing, or a related field.
•    Strong expertise in satellite remote sensing, including atmospheric correction techniques.
•    Proficiency in R, Python, or MATLAB for data processing, geospatial analysis, and statistical modeling.
•    Experience with time series analysis, spatial mapping, and oceanographic data interpretation.
•    Experience in writing scientific papers and presenting research results.
•    Ability to work independently and collaboratively in an interdisciplinary research environment.

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