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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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computing, and digital twin technologies for mission autonomy and predictive analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission
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and cutting-edge research. Job Description We are seeking a postdoctoral researcher specializing in digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems
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partners, and monitoring budgets. Required Qualifications : PhD: A PhD in digital public health, urban health, data science applied to health or urban planning, smart urban systems, or a related field
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, participate in grant writing activities, and seek external funding opportunities to support ongoing research projects. Contribute on the group’s activities in processing of sustainable materials, (bio)polymer
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to the multidisciplinary character of ACER CoE, the ideal candidate must have as well a multidisciplinary scientific profile: PhD degree in Materials Science, Chemical Processes or another suitable engineering discipline
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: PhD degree in Materials Science, Chemical Processes or another suitable engineering discipline. Sound background in Electrochemistry/Chemical & Mineral Processes/Chemistry Experience in the recovery
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activities in processing of sustainable materials, (bio)polymer composites and their applications. Participate in the supervision of undergraduate, master’s, and doctoral students. Criteria of the candidate
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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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digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems in real time. The candidate will contribute to modeling interactions between physical and digital