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radiation and using Monte Carlo simulation software (MCNP, GEANT4). Knowledge of multi-element analytical techniques (PIXE, XRF, ICP-MS). Valorization of Industrial Waste: Experience in developing processes
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assessment in urban environments. Proficiency in hydrological modeling software (SWMM, HEC-RAS, or equivalent). Experience with GIS tools (ArcGIS, QGIS) for spatial analysis and mapping of water flows and risk
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. • Strong expertise in geospatial data analysis and machine learning techniques applied to Earth Observation data. • Proficiency in geospatial software and platforms such as QGIS, ArcGIS, or Google Earth
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to Earth Observation data. • Proficiency in geospatial software and platforms such as QGIS, ArcGIS, or Google Earth Engine. • Programming skills in Python or similar scientific computing environments
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research outputs. Good English (written & oral) and willingness to collaborate with agronomists and partners. Preferred Postdoc or ≥2 years research experience after PhD; first-author publications in
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Proficiency in using simulation software for process modeling (e.g., ASPEN, SuperPro Designer…). Familiarity with scaling up biotechnological processes and designing pilot-scale plants. Ability to analyze
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dynamic) using simulation software such as Aspen Plus, gPROMS, or COMSOL Multiphysics. Solid understanding of process control strategies, including model predictive control (MPC), nonlinear control, and
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on the manipulation of most of those instruments; Experience in the use of academic databases (CCDC, RCSR, ...) and softwares (Material Studio, Diamond, Origin, ....); Evidence of experience in adsorptive or/and
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(CCDC, RCSR, ...) and softwares (Material Studio, Diamond, Origin, ....); Evidence of experience in adsorptive or/and membrane separation technologies. Applications must be submitted online in a single
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tools (CPLEX, SAP). Experience with data analysis software. Soft Skills Analytical mindset and attention to detail. Ability to manage priorities and work under pressure. Excellent communication skills and