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molecular biology to explore and validate the potential of microalgae in controlling soilborne pathogens. This position offers an exciting opportunity to work at the interface of applied microbiology and
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Materials Research Center (SusMat-RC) at UM6P. The successful candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models
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will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell lines). Designing, establishing protocols and conducting recombinant
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maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high-impact research in top-tier conferences and journals
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proteins. Under the supervision of the project leader, your responsibilities will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell
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experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high
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technologies, solar thermal integration, and system optimization. Responsibilities will include laboratory investigations, prototyping, field testing, and performance analysis of water harvesting systems across
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technological research clusters in the fields of materials and nanomaterials, biotechnology, microelectronics and life sciences. Its work is geared towards applied research and innovation to meet market needs
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, optimize, and operate bioreactors, digesters, and other equipment. By employing advanced techniques like sensitivity analysis and process simulations, the candidate will improve yields and energy efficiency
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fertilizers. Demonstrated experience in either agronomic testing or material development, with willingness and ability to work across disciplines Experience in the development and characterization of glass