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-based environments for high-performance data analysis. Knowledge of biological network inference, causal modeling, and graph-based AI approaches. Experience in multi-modal data fusion, representation
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(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal
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related to geomechanics and rock stability. Qualifications: Ph.D. in mineral engineering, geological engineering or a closely related field. Proven track record of securing research funding Experience in
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, geological engineering or a closely related field. Proven track record of securing research funding Experience in supervising graduate students and leading research teams. Excellent communication and
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. Track record of high-level scientific publications and presentations at international conferences. Commitment to research excellence. Interest in African development challenges. Entrepreneurial mindset
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, Economics, Finance, Business, Public Policy, or a related field. A strong research background is essential, demonstrated through a proven track record of academic publications in ESG-related disciplines
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management including milestones tracking, project finance & contracts development, technology licensing and commercialization. Minimum of 3 years of teaching experience post- graduation in a university set
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essential, demonstrated through a proven track record of academic publications in ESG-related disciplines. The candidate must also have experience in teaching and course development at the university level
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organizational skills. Good publication track record in peer-reviewed journals with respect of the career development.
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communication skills in English and French, both written and verbal. A track record of publication in well ranked journals. Established collaborations with renowned international researchers in the field