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experimentation, modeling, simulation, and optimization of chemical processes. The successful candidate will work on the development of advanced process models combining experimental investigations with
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vanadium for energy storage applications. Applying thermodynamic modeling tools (CALPHAD, FactSage) to simulate vanadium phase behavior and guide process improvements. Performing advanced characterization
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Modelling and Simulation”. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/412392/asari-postdoctoral-… Requirements Additional Information STATUS: EXPIRED X (formerly Twitter
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and grey-box modeling) to enable predictive simulations of chemical and biochemical processes. Construct multi-objective optimization frameworks (Pareto optimization) to evaluate trade-offs among
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to its state-of-the-art infrastructure. With an innovative approach, UM6P places research and innovation at the heart of its educational project as a driving force of a business model. In its research
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regarding the production of targeted crops in Africa, work with the project team and valorize data as review publications. Develop and implement simulation models to predict yields from secondary data sources
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focused on Artificial Intelligence (AI)-driven retrosynthesis and reaction prediction. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic
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at the heart of its educational project as a driving force of a business model. In its research approach, the UM6P promotes transdisciplinary, entrepreneurship spirit and collaboration with external institutions
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
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. Key duties
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: Chetelat, B., Gaillardet, J., Chen, J.Bin, 2021. Dynamic of boron in forest ecosystems traced by its isotopes: a modeling approach. Chem. Geol. 560, 119994. https://doi.org/10.1016/j.chemgeo.2020.119994