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city models focused on health and environmental infrastructures. Advanced Data Analysis: Advanced skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban
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contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
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Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and applying AI/ML models to energy systems or similar applications. Proficiency in
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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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, Operations Research, Data Science, or a related field. Advanced expertise in Operations Research. Strong skills in Machine Learning. Practical experience in mining or industrial environments (through projects
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of UAV demonstrators at UM6P and OCP sites. Methodology: AI Development: Reinforcement learning, computer vision, and sensor fusion for autonomy. Digital Twin & Edge Computing: Implement real-time
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skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban Health Principles: Familiarity with urban planning principles centered on health (active mobility
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and implement innovative image analysis methods to quantify plant characteristics. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and
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) combined with machine learning and chemometrics. Key Responsibilities: The Postdoctoral Researcher is primarily intended to support leaf spectroscopy research but will also be involved in other research
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teach undergraduate and/or graduate students on marine biology, seaweeds cultivation, and aquaculture, as well as special courses related to the candidate's specialization. Supervise M.Sc. and PhD