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a two-year research project in collaboration with international academic partners. The main objective of the project is to study the interaction between machine learning and wireless communication
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and real-time data acquisition systems. Participate in testing and deployment of UAV demonstrators at UM6P and OCP sites. Methodology: AI Development: Reinforcement learning, computer vision, and sensor
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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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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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at conferences, and stakeholder engagement sessions. Required Qualifications: A Ph.D. in Climate Science, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications 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