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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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design. Objectives: The main objective is to support the development and validation of morphing drone prototypes by combining structural optimization, lightweight design, and experimental testing
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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
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kinetics principles. Key Responsibilities: Develop and optimize adsorbent catalytic materials (e.g., heterogeneous catalysts, supported metal catalysts, photocatalysts). Design experimental setups for gas
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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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treatment experiments (e.g., calcination, roasting, smelting), and optimization of pyrometallurgical flow sheets for the production of value-added materials or metals.The selected candidate will contribute
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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
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dedicated to advancements in sustainable energy through innovative research and training. Our focus lies in the design, development, and optimization of inorganic materials for various sustainable energy
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design and very good programming skills (Python, Pytorch). Excellent command of IT tools and perfect command of AI and Data Science tools. Profile required: PhD in computer science, specializing in AI and
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, 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