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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities
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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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few meters), suitable for plot-scale applications. Surface soil moisture can in turn be used to estimate root zone soil moisture via land surface models that enable linking the surface to root zone
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efficiency, ion separation rates, energy consumption, etc. Model ion transport and system behavior under different operational conditions. Collaborate with researchers in diverse projects and contribute
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during natural disasters. AI models can process big datasets efficiently, helping to make informed, unbiased decisions, and ensuring resources are distributed to those most in need. Additionally, when
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. without vegetation. Studying dust deposition and its impact on energy performance. Analyzing meteorological, soil, and energy production data. Contributing to the modeling of PV performance under local
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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Osmosis (FO) — Reverse Osmosis (RO) system. The work of this project includes lab work, computer modelling, life cycle assessment, and techno-economic study. The project will contribute to protecting water
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research and innovation at the heart of its educational project as a driving force of a business model. In its research approach, the UM6P promotes transdisciplinary thinking, an entrepreneurial spirit, and
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the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor master students and PhDs Education, qualifications, and experience Applicants must have an earned doctorate in Agronomy