200 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Morocco
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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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) Country Morocco Application Deadline 2 Oct 2026 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical
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diagnosis. These tools will leverage various spectroscopic techniques (VNIR, SWIR, and XRF) combined with machine learning and chemometrics. Key Responsibilities: The Postdoctoral Researcher is primarily
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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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) Country Morocco Application Deadline 1 Oct 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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are hiring a postdoctoral researcher to work on rethinking extraction methods at one of OCP Group’s production sites. The project will rely on Operations Research and Machine Learning approaches. The objective
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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
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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