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coatings, to protect the LFP particles while optimizing their performance in high-energy-density applications. The coated LFP materials should exhibit superior mechanical and chemical resilience, ensuring
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to microclimatic variations induced by local vegetation. The researcher will contribute to the analysis of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic
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, the validation is monitored through design of experiments and optimization of workflows much more rapidly than conventional approaches. The HTMR is a 100% Applied Sciences research laboratory, and is setting up
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experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high
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monitoring and electric vehicle battery tracking. Integrate environmental and energy sensors with real-time data collection and analysis systems. Deploy prototypes in the field and optimize their performance
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. Skilled in analytical methods for catalytic/separation agents materials characterization. Solid understanding of chemical kinetics principles. Key Responsibilities: Develop and optimize adsorbent catalytic
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advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
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of water intended for agricultural use. The selected candidate will contribute to the development and optimization of desalination processes (membrane-RO), the analysis of treated water quality (especially
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Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic
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research team. The successful candidate will work on optimizing methods for nanofibers extraction from various types of biomass, focusing on the development of efficient, sustainable, and scalable processes