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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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material quality. The resulting models will act as a predictive tool for process optimization and design improvements, providing a foundation for scalable industrial applications. Job Description: The
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: Sustainable mineral processing and hydrometallurgy, with emphasis on potash beneficiation, process optimization, and potash brine valorization. Main responsibilities: Conduct literature review on potash ore
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, process optimization, and potash brine valorization. Main responsibilities: Conduct literature review on potash ore processing (carnallite) and brine management practices; Perform mineralogical and chemical
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collection and analysis systems. Deploy prototypes in the field and optimize their performance based on feedback. Guarantee the reliability, security and scalability of the IoT solutions developed. Work
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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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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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structures, integrating morphing wings and additive manufacturing processes for high-performance and energy-efficient drones. Keywords: Morphing wings, composites, additive manufacturing, aerodynamics, UAV
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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 The successful
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Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply their expertise to advance predictive