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Machine Learning models for quality prediction and control of phosphate ore. Simulating and evaluating various extraction scenarios, considering industrial constraints. Collaborating closely with field and
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under investigation. Job Description: The position is open to candidates with a PhD or equivalent in a relevant discipline from a recognized university. Applicants must demonstrate that their doctoral
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is also mandatory. Candidate Profile: Hold a PhD in catalytic processes or an equivalent in a relevant field Possess relevant experience in CO2 hydrogenation Demonstrate experience in gas-phase product
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innovative approaches to minimize cell polarization by precisely controlling electrolyte transport properties both in the bulk and across interfaces. Develop novel electrolyte chemistries aimed at directing
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/electrolyte interfacial structure-property relationships to gain deeper insights into material behavior. Develop innovative approaches to minimize cell polarization by precisely controlling electrolyte
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publications and contribution to collaborative proposals. Support of graduate student mentorship and lab coordination. Required Qualifications & Experience PhD in Materials Chemistry, Extractive Metallurgy
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using advanced geological modeling tools such as Datamine software, Leapfrog Geo and Surfer. Supervise MSc/PhD students working on related tasks. Publish high-impact papers and contribute to funding
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management and quality control practices. Foster collaborative linkages with other programmatic areas, core scientific teams, and external partners to strengthen conceptual frameworks and accelerate cross
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at scientific meetings and conferences. Co-supervise ungraduated, graduate and PhD students Participate in developing research proposals and programs in the area of collaboration with multidisciplinary
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), overall health, and more. For instance, in electric vehicles, the BMS carries out functions such as monitoring, controlling, optimizing, and ensuring safety to mitigate potential hazards related to battery