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computational model to capture the complex transport of gases, liquids, and charges in these porous structures, including the complex interfaces between them. Insights from the model will directly guide the
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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for implementing ONNs. Modeling, simulate and benchmark different computing tasks such as combinatorial optimisation tasks and solving partial/ordinary differential equations with ONNs. Design and tapeout ONN chips
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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the experimental results in physical models describing the observed processes. The PhD work embedded in the Topsector program Urban Energy and aims to contribute to local grid balancing, and increased efficiency
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to help accelerate the energy transition