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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities
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distribution. Spectroscopic techniques (XPS, Raman, FTIR) for surface chemistry studies. Electrochemical Performance Evaluation: Galvanostatic cycling to assess capacity retention and rate capability
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. Structural and Chemical Characterization using: X-ray Powder Diffraction (XRD) and Rietveld refinement for phase analysis. Electron microscopy (SEM, TEM, EDS) for morphology and elemental distribution
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non-iidness of data distribution, system heterogeneity, and dynamic environments. Key duties: The Postdoctoral Fellow is expected to: Publish in high-impact journals in the field. Supervise graduate and
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conditions. Implementing a multimodal approach for large-scale data analysis using CPU and GPU Solutions at the UM6P Data Center. Innovate and improve image analysis algorithms for plant trait quantification
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of the geochemical processes governing the formation, enrichment, and preservation of sedimentary phosphate deposits and associated sediments. A particular emphasis will be placed on the distribution, speciation, and
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concentration, and the air flow rate. However, the extrinsic parameters include the properties of the ore to be floated, namely its particle size distribution, the degree of mineral liberation, mineral
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. Proficiency in programming MATLAB and Python for data analysis and algorithm development. Knowledge of data assimilation techniques is a valuable added. Excellent communication skills and ability to work
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communication resources to train the federated machine learning model efficiently. She/he will investigate realistic scenarios including non-iidness of data distribution, system heterogeneity, and dynamic
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refinement for phase analysis. Electron microscopy (SEM, TEM, EDS) for morphology and elemental distribution. Spectroscopic techniques (XPS, Raman, FTIR) for surface chemistry studies. Electrochemical