158 phd-mathematical-modelling-ecological-modelling Postdoctoral positions in Morocco
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business model. About Entity (Hiring entity): We are seeking a highly skilled and motivated postdoctoral fellow to join us with specialty in photovoltaics and the investigation of photoluminescence in
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Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic
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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
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling
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, Applied mathematics, or related field. Strong background in land surface modeling, remote sensing data analysis, images processing, and geospatial analysis. Experience working with satellite imageries (e.g
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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
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proposals and presentations. Requirements: Specify the required qualifications and experience for the position. This might include A PhD in a relevant field such as mechanical engineering, materials science
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postdoctoral researcher specializing in Urban Energy Networks Management, with expertise in developing innovative models to optimize energy consumption in residential sectors, electric mobility, and urban
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-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. About Entity (Hiring entity): MAScIR
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, Data Science, Climate Science, Geoinformatics, Applied and Computational Mathematics, or related fields. Proven experience in developing deep learning models (e.g., CNNs, RNNs, LSTMs) for large-scale