119 phd-architecture-building Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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in related program areas to gain exposure to and build knowledge on experimental/research activities and approaches, in order to improve conceptual development and industrial implementation. Identify
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transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
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, tunable porosity, and chemical versatility. These properties make them excellent candidates for detecting various analytes in liquid media, including heavy metals, organic pollutants, biomolecules, and
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with the core scientific personnel in related program areas to gain exposure to and build knowledge on experimental/research activities and approaches, in order to improve conceptual development and
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. Mentor graduate students and participate in capacity-building activities within the research team. Required Qualifications: Ph.D. in Chemistry, Computational Chemistry, Cheminformatics, Computer Science
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and technological advancements. Located in the Green City of Benguerir, the university aims to make a lasting impact nationally, continentally, and globally by fostering interdisciplinary collaboration
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algebra methods targeting large-scale HPC systems. Optimization of linear algebra libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications
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. Prepare and submit high-impact scientific publications and present results at international conferences, workshops and meetings. Mentor master’s and PhD students as part of research activities. Collaborate
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. Contribute to scientific publications and disseminate results to decision-makers and communities. Qualifications required PhD in one of the following fields: electronics and embedded 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