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and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have recently completed (or be close to completing) a PhD in
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, qPCR, sequencing) for the identification and phylogenetic analysis of microalgae and target pathogens. Supervise and mentor MSc and PhD students involved in related research activities, providing
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presentations; Collaborate with internal teams, partner laboratories, and industrial stakeholders. Candidate Profile: Required qualifications : PhD in Mineral Processing, Hydrometallurgy, Chemical Engineering, or
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selected in accordance with this and expected to be in the upper segment of its class with respect to academic credentials. Candidate must hold a PhD in synthetic organic chemistry and must have: Clear
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Profile: Required qualifications : PhD in Mineral Processing, Hydrometallurgy, Chemical Engineering, or related discipline; Proven experience in ore characterization and process development; Strong
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required; proficiency in French is a plus. Preferred Qualifications Experience in pyrochimical processing of oxide, sulfide, or silicate ores. Familiarity with thermodynamic simulation software (e.g
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, including their potential applications in agriculture. Proficiency in experimental design, data analysis, and statistical software. Excellent written and oral communication skills, with a proven track record
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: PhD degree in Materials Science, Chemistry, Crystallography Knowledge in crystallization technics Expertise in solving crystal structure using single-crystal X-ray diffraction data. Experience in
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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to the chemical and Process Engineering stream. The candidate will also be expected to participate in UM6P's collective projects and external missions, and to provide support to students (PhD and Master), i.e