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Collaborate with domain experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
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: The candidate must have: PHD with skills in one of the following fields: history, philosophy, anthropology, sociology, psychology Rigor / motivation, Good communication skills, Teamwork An appropriate scientific
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Chemistry, Materials Science, or a related field with a with hands-on fertilizer manufacturing process and formulation. Experience in designing and characterizing simple and complex fertilizers Good knowledge
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, Environmental Engineering, or related discipline from a recognized University. Strong expertise in lipid extraction and biodiesel production Good written and spoken English as well as presentation skills
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dynamics, preferably for bioreactor environments Have knowledge and familiarity with aerobic and anaerobic treatment Good written and spoken English as well as presentation skills Excellent interpersonal
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to mentor students and other personnel. Energetic, motivated, and proactive. Good publications record in refereed journals Fluency in written and spoken English. French and Arabic will be a plus Experience in
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IWRI - Postdoctoral Researcher in Bioinspired Circular Conversion of Multi-source Biomass Feedstocks
scientific papers and deliver technical reports. Good publication track record in peer-reviewed journals. Strong communication skills in English (written and oral). Ability to work independently and as part of
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in Computational Biology. The candidates should be highly motivated and have a Ph.D. in computational biology or any related field, and a good knowledge of molecular biology. The candidate will be part
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applied urban and environmental challenges. • Good organizational and time-management skills. • Ability to communicate complex results clearly to both scientific and non-scientific audiences