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machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and academic experts to ground-truth results. Dissemination Publish in
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at the intersection of AI, NLP, and industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning
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landscapes. Collaborate with multidisciplinary teams to integrate remote sensing data with ground-based observations, physical algorithms, and machine learning models. Participate in field data collection and
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-based observations, physical algorithms, and machine learning models. Participate in field data collection and validation to support model accuracy. Publish research findings in peer-reviewed journals and
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of the orientations of the Center for African Studies: health. The candidate will collaborate with the Medical School. He /She has to be able to teach in English medical ethics. Responsabilités et taches prévues
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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oriented institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
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concepts and profitability. In-depth knowledge of environmental sustainability standards. Experience with data prediction and classification techniques. Computer Skills Good proficiency with optimization
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Agriculture Research Institute (ASARI) - Laayoune About UM6P: Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system