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scales. The project involves the modelling of energy infrastructures, the development of scenario-based simulations, and the generation of actionable indicators to support decision-making. You will be part
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contexts. Additional experience in industrial ecology, material flow analysis, and in particular energy systems modelling, simulation, and mobility will be considered a strong asset. The candidate shall be
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(e.g., including simulation, prediction). Enable the evolution of integrated data/models all along the Digital Twin lifecycle Ensure the consistency of integrated data and models with regard to potential
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actively contribute to the WeForming and EnerTEF projects. WeForming and EnerTEF propose developing automatized and intelligent solution for operating active distributed grids with multiple active asset6s
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farm-scale modelling of nutrient flows. Food security, climate change and loss of biodiversity represent three of today’s major societal challenges. Finding solutions for all these challenges requires
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experimental data gathered and processed by a doctoral candidate in the project, you will extend the existing open-source Model of Explicit Cross-section Hydraulic Anatomy (MECHA) to simulate water and solute
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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data-driven models, mixing knowledge about human modelling, the driver-car-tire system and its environment, with telemetric and physiological data gathered from a world-leading car simulator. Your role