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                at the intersection of AI, NLP, and industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning 
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                recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs 
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                the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Location: School of Architecture, Planning and 
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                and contribute to the overall research mission of the group. Position Requirements PhD (completed or near completion) in Electrical Engineering, Computer Science, Physics,Applied Mathematics, or a 
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                Requirements PhD (completed or near completion) in Electrical Engineering, Computer Science, Physics,Applied Mathematics, or a related field. Strong background in one or more of the following: quantum 
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                21 Aug 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Computer science Engineering Researcher Profile Recognised Researcher (R2) Established Researcher 
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                learning architectures suitable for deployment on resource-constrained robotic systems. The postdoc will have access to state-of-the-art computational resources. Key Responsibilities: Develop novel methods 
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                incubation and start-up ecosystems. About the recruiting Entity The College of Computing is a central component of the University Mohammed VI Polytechnic (UM6P) with campuses in Benguerir and Rabat. The goal 
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                . Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud). Understanding of BMS architecture and electric mobility systems. 
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                for parallelism in the tensor completion process to enhance computational efficiency. Investigate parallel algorithms and architectures that can exploit the inherent parallelism in tensor operations. Collaboration