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highly skilled and motivated Postodoctoral Scientist with advanced expertise in isotope-enabled ecohydrological modeling. We are looking for an early career scientist who is passionate about unraveling the
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continent. Profile: Post-doctoral fellow in Artificial Intelligence - Large Language Models and BDI Systems Ai movement is recruiting a post-doctoral fellow in Artificial Intelligence - Large Language Models
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-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex chemical and biochemical processes. The research will contribute to next-generation smart
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impeller performance, analyze hydrodynamic characteristics, and identify key synthesis parameters influencing material quality. The resulting models will act as a predictive tool for process optimization and
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, patents, and proprietary sources to train and validate predictive models. Integrate retrosynthesis tools with cheminformatics platforms and molecular modeling software. Collaborate with synthetic chemists
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of related start-ups. For more information about our Center, please visit our webpage: https://vanguard.um6p.ma/ Offer description: There are many systems of interest to scientists that are composed
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system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting
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networks, metabolic networks) to identify key disease drivers and biomarkers. Build predictive models for disease classification, patient stratification, and treatment response prediction. Collaborate with
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challenges for water sustainability. Job description: The IsoTrace team is seeking a highly skilled and motivated Postodoctoral Scientist with advanced expertise in isotope-enabled ecohydrological modeling. We
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage