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. Process simulation, cost, life cycle, and social assessment of CCUS value chains. Reactor design, optimization, and sizing using phenomenological and/or CFD methods. Energy system analysis. Strong
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
-dimensionality and complexity of metabolomics data, requiring advanced AI/ML techniques for robust analysis and interpretation. Integration of multi-omics data (genomics, transcriptomics, proteomics, and
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to microclimatic variations induced by local vegetation. The researcher will contribute to the analysis of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic
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data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model parameters and improve predictive accuracy. Contribute to code development, documentation
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. Analysis of vegetation effects on microclimate. Participation in the analysis of soil–plant interactions (composition, moisture, microbiology). Scientific valorization: publications, reports, and
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of materials, Porous adsorbents, X-ray crystallography, Spectroscopy, and Topological analysis of inorganic and organic-inorganic hybrid coordination polymers. Job description: The Applied Chemistry
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analysis of inorganic and organic-inorganic hybrid coordination polymers. Job description: The Applied Chemistry and Engineering Research Centre of Excellence (ACER CoE) at Mohammed VI Polytechnic University
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software tools related to materials/process modeling, thermochemical systems, statistical design (DoE), and data analysis. Excellent verbal and written communication skills. Solid understanding
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communities in soil environments. Develop and optimize laboratory protocols for characterization, and functional analysis of soil biology. Utilize high-throughput sequencing technologies to analyze soil
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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