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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
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to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials
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of computational tools for process monitoring and predictive analysis Candidate Criteria Applicants should have: A PhD in Process Engineering, Chemical Engineering, or a closely related field Strong expertise in
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digital twins for industrial chemical processes Process optimization and model-based decision support tools Development of computational tools for process monitoring and predictive analysis Candidate
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the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor master students and PhDs Education, qualifications, and experience Applicants must have an earned doctorate in Agronomy
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interfaces, and condensation surfaces under varied operating scenarios. Develop and refine performance simulation models and predictive tools to support system optimization and deployment strategies. Prepare
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; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor