118 software-testing-short-course Postdoctoral positions at MOHAMMED VI POLYTECHNIC UNIVERSITY in Morocco
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of the AI algorithms. Key duties Develop a robust framework to simulate streamflow decomposed into fast-flow and baseflow at multiple Moroccan watersheds. The candidate would have to test various fast-flow
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of software tools for the broader research community. Responsibilities: Develop and implement transformer-based genomic language models for bacterial genome analysis. Train and evaluate models on large-scale
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, XRD, SEM, TGA, BET). Good Knowledge of agronomic tests and design of experiments (DOE). LCA basics Track record of publications in peer-reviewed journals. Strong analytical and problem-solving skills
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operate lab-scale BMED setups, including multi-compartment electrochemical cells. Test and characterize membranes: transport properties and selectivity. Monitor and analyze system performance: current
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): Knowledge of flotation processes, especially for industrial minerals such as phosphate. Familiarity with principles of green chemistry and renewable resources. Ability to design and carry out flotation tests
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. Strong knowledge of heterogeneous catalysis and computational chemistry. Experience with computational modeling (i,e, DFT, and/or molecular dynamics). Familiarity with software such as Material Studio
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and thus regulate the Earth’s global climate at short time scales. In its 2022 report for policymakers, the Word Resource Institute (Seymour et al., 2022) draws attention to the fact that forests do not
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, testing, and demonstration of novel CCUS technologies Process simulation, cost, life cycle, and social assessment of CCUS value chains Reactor design, optimization, and sizing using phenomenological and/or
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characterization of porous functional materials such as MOFs and MOF composites as well as the fabrication of different nanoparticles Able to examine the textural and structural changes of porous material catalysts
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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