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values across different omics layers and platforms. Cross-omics data fusion and representation learning for comprehensive systems biology modeling. Identification of causal relationships and biomarker
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to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and predict key climate variables such as precipitation and temperature which are essential
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the agricultural, environmental and health sectors. The lab also provides bioinformatics consulting and data management services to UM6P researchers and their collaborators. UM6P has state of the art NGS sequencers
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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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Machine Learning models for quality prediction and control of phosphate ore. Simulating and evaluating various extraction scenarios, considering industrial constraints. Collaborating closely with field and
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Climate. Collaborating with students, postdoctoral fellows, and visiting scholars worldwide, the Centre is committed to training a new generation of African Atmospheric Scientists and faculty members
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science, and sustainability. Driven by innovation, sustainability, and interdisciplinary collaboration, the center aims to bridge research and practical applications for the development of a large spectrum
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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 of Morocco and Africa
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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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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