124 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY
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and implement innovative image analysis methods to quantify plant characteristics. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and
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foundation in catalysis/ separation and chemical/process engineering. The successful candidate will significantly contribute to the conception, synthesis, and evaluation of separation/catalytic systems aimed
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Osmosis (FO) — Reverse Osmosis (RO) system. The work of this project includes lab work, computer modelling, life cycle assessment, and techno-economic study. The project will contribute to protecting water
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Polytechnic University aspires to leave its mark nationally, continentally, and globally. About the Chemical & Biochemical Sciences Green Process Engineering (CBS) The Chemical & Biochemical Sciences Green
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About Mohammed VI Polytechnic University (UM6P) Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system
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Discipline: Process Mineralogy, Mineral Processing, Artificial Intelligence Duration: 12 months, with the possibility of renewal for an additional 12 months Institutions: UM6P-Benguerir/ Mineral-X
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nationally, continentally, and globally. About CBS: The Chemical & Biochemical Sciences, Green Process Engineering (CBS) department is a component of Mohammed VI Polytechnic University (UM6P). CBS aims
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processes. This project focuses on designing and optimizing novel materials that enhance the efficiency and effectiveness of converting biomass into valuable products such as biofuels and fine chemicals. We
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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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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