132 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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Post-Doctoral Fellow Position: Development of innovative biomass processing for nanofibers extraction 13219 Position Summary: We are seeking a motivated and skilled Postdoctoral Fellow to join our
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Post-Doctoral Fellowship in the development of catalytic materials for CO2 hydrogenation to high-value products About UM6P: Located at the heart of the future Green City of Benguerir, Mohammed VI
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Post-doctoral fellowship in the development of MOF catalysts for photocatalytic CO2 conversion and water splitting Mohammed VI Polytechnic University (UM6P) - Chemical & Biochemical Sciences CBS
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to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict
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committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development of Morocco and Africa. More than just a traditional
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The Chemical and Biochemical Sciences-Green Process Engineering at the University of Mohammed VI Polytechnic Benguerir Morocco seeks Postdoctoral applicants in Proteomics and Drug Development. Job
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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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