-
axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate–water–energy–agriculture interactions, with applications
-
, particularly for multi-variable simulations. Knowledge of complex systems modeling applied to urban dynamics. Publications in scientific journals. Personal and Organizational Qualifications: Ability to develop
-
-driven frameworks for multi-scale modeling, multi-objective optimization, and predictive control of complex chemical and biochemical processes. The research will contribute to next-generation smart
-
biochemical reactions to scale-up and validation of process engineering. CBS projects aim at an in-depth understanding of the molecular mechanisms of all transformations in order to propose new original
-
The successful candidate will contribute to the following research axes: AI-driven territorial diagnostics and foresight, integrating multi-source satellite data with machine learning and spatial modeling Climate
-
equilibrium modeling in multi-component systems. Comprehensive use of characterization tools, including: SEM, TEM, HAADF-STEM, XRD, and EDS for micro- and nano-scale phase analysis. LA-ICP-MS for ultra-trace
-
for the co-precipitation of FePO₄/LiFePO₄ in CSTRs. The work will involve building multi- scale CFD frameworks that integrate hydrodynamic simulations, chemical kinetics, and thermal transport models
-
(especially libraries 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