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. Area of Research: Sustainable mineral processing, with emphasis on phosphates beneficiation and process optimization. Main responsibilities: Conduct literature review on phosphate ore and waste
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. The candidate will contribute to the mechanical design, composite fabrication, and experimental validation of UAV structures, integrating morphing wings and additive manufacturing processes for high-performance
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development. With its state-of-the-art campus and infrastructure, this unique nascent university has woven a sound academic and research network, and its recruitment process is seeking high-quality academics
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-products. Monitor and control the migration of radionuclides and heavy metals throughout industrial processes. Optimization of Industrial Processes: Utilize nuclear techniques to enhance the efficiency and
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials. Key duties The successful candidate is expected to: Build and evaluate chemical databases
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and carbon footprint. Activities and Responsibilities Optimization and Improvement of Logistics Processes Analyze routing, storage, and loading flows. Identify optimization levers to reduce costs and
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, and Sustainable Process Engineering. The researcher will join a multidisciplinary research program aimed at optimizing natural graphite for Li-ion battery applications, developing sustainable
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. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and
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. Process simulation, cost, life cycle, and social assessment of CCUS value chains. Reactor design, optimization, and sizing using phenomenological and/or CFD methods. Energy system analysis. Strong
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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