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implement an integrated, data-driven digital twin of the national energy system, capable of simulating and analyzing multi-energy infrastructures (electricity, heat, gas, hydrogen) across spatial and temporal
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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properties are attributed to light capture for photosynthesis and radiative heat dissipation for temperature management, whereas the role of structural leaf surface properties, such as the presence of bumps
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experimental and numerical approaches. Materials classes of interest include components (monomers, polymers, additives, (nano)particles, etc.) utilized in high-performance polymeric materials with relevance in
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electrical engineering, automation, computer engineering, or a closely related discipline, with proven expertise in the operation and control of intelligent energy systems. Experience and skills Solid
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was originally developed to simulate water and solute transport in roots, part of this task will be to introduce gaseous transport of water and CO2, and transitory starch pools. Model development will be performed
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Pneumatic Tires, Structure-Process-Properties Relationships. How will you contribute? Do you have proven skills in data analysis, machine learning, as well as in mathematical and computational modelling? You