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solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high-impact research in top-tier
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mining waste deposits (MATs). This project integrates mineralogical and mechanical characterization, pilot-scale testing, and advanced process simulation, with the objective of optimizing grinding
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techniques (e.g., DNA/RNA extraction, PCR, qPCR, metagenomics, transcriptomics) to study microbial communities in soil environments. Develop and optimize laboratory protocols for characterization, and
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computing and machine learning. The research will emphasize both theoretical advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more
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optimize composite materials that can significantly enhance the efficiency of wastewater purification processes by leveraging the piezocatalytic phenomenon an emerging technology with great potential
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the innovative use of piezocatalysis. The successful candidate will engage in cutting-edge research to understand, design, and optimize composite materials that can significantly enhance the efficiency
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and structural analysis Cheminformatics and chemical data mining Computational catalysis or process optimization AI applications in analytical, organic, inorganic, or physical chemistry Automation in
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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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characterization. Conduct research to design, develop, and optimize sensors for industrial applications. This includes exploring novel sensing technologies, materials, and data analysis techniques. Conduct rigorous
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in Statistial models for optimizing the chemical process Skills in elemental & structural analysis using various existing techniques. Knowledge in advanced structural characterizations will be valued