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Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools
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like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. • Advanced skills in predictive modeling and machine learning, particularly for multi-variable simulations. • Knowledge of complex systems
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Positions: two postdoc positions in the development of electrodes materials for ultrahigh performance of metal-ion batteries via advanced multi-scale computational modeling About UM6P: Located
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network management systems (smart grids, microgrids). • Expertise in energy flow analysis and simulation, including production, storage, and consumption. • Experience in scenario modeling for various
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engineering, and particularly in modeling, simulation and optimization of the phosphate value chain processes. In terms of research, the candidate will reinforce the team of the CBS department. His/her
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engineering, computer science applied to urban infrastructure, data science, or a related field. • Expertise in numerical modeling and simulation for urban systems. • Proficiency in digital twin tools and
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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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risk management, urban planning, energy engineering, and other relevant disciplines to develop integrated solutions. • Modeling and Simulation: Use simulation and modeling tools to analyze and
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design simulation studies using water, soil and crop modeling tools Compile and analyze experimental data, interpret results, prepare presentations and manuscripts, and publish in high-quality peer
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determinants of urban health. • Predictive Modeling Skills: Ability to develop predictive models and simulation tools to assess the impact of urban interventions on health. • Smart City Experience