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, land-use change, and environmental dynamics. • Design and implement spatial analytics and geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and
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geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and geospatial data analysis techniques to large Earth Observation datasets. • Produce high-quality
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated
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, Morocco, is seeking for a postdoctoral candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related fields. The candidate is expected
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COLCOM: The School of Computer Sciences at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco, is seeking for a postdoctoral candidate in the area of machine learning for IoT networks
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
Computational Chemistry, Materials Science, or a related field. Strong background in computational chemistry techniques, including molecular dynamics, quantum mechanical simulations, and machine learning
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fields. The successful candidate will answer questions such as how to assign limited communication resources to train the federated machine learning model efficiently. She/he will investigate realistic
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techniques (FTIR, NIR, Raman, …) with machine learning/ chemometrics. Responsibilities of the Position The Postdoctoral researcher is intended to support the soil spectroscopy research activities and digital
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The successful candidate will contribute to the following research axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate