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satellite remote sensing, data assimilation, atmospheric inverse modelling, emission estimation, and atmospheric modelling. Candidate Profile The ideal candidate will have a strong academic background
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. Background and Objectives As part of the project titled “Development of an Intelligent Geospatial Interface for Panel 8 of the Benguerir Phosphate Mine: Integration of Multidisciplinary Data,” we are
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to enhance data-driven decision-making, adaptability, and safety within agriculture systems. AI Knowledge for Agriculture: Build LLM and NLP tools, and open-source dataset for agriculture use
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atmospheric modelling. Experience in data processing and integration of multi-instrument datasets. Knowledge of pollutant formation, transformation, transport, and fate. Experience in pollutant
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Mohammed VI Polytechnic University ( https://www.um6p.ma/en ) is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its
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based at various sites to interpret the data from the UM6P Stations and other global data sets and with the wider team members including postdoctoral research associates and PhD students. Where to
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postdoc, you will delve into genomics and metagenomics data to dissect the signaling systems of plant-associated bacteria and analyze the genomic features of beneficial bacterial strains. This is a
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highly monitored since 2008 with an eddy-covariance flux tower together with numerous ancillary data related to water, carbon and nutrient cycles (Christina et al. 2017). The soils at this site are deep
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exciting research topics are proposed (not limited): Computer Vision / Remote Sensing for Agriculture: Explore the application of computer vision and remote sensing techniques to enhance data-driven
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/vapor/liquid separation systems, adsorption modeling, and data analysis. Hands-on experience in adsorbent material structuring/shaping (e.g., extrusion, pelletization, electrospinning) is highly