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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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supports, nitride-based materials, and hierarchically structured porous materials for CO2 hydrogenation reactions using photo- or thermal catalysis. The successful candidate will be involved in optimizing
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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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for teamwork, problem-solving, and collaborative relationships Strong technical background in at least one of the following areas: Mathematical optimization, Resource allocation, Machine learning, Wireless
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transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
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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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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
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digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems in real time. The candidate will contribute to modeling interactions between physical and digital
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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