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anharmonic DFT calculations of PAHs available in the team You will implement neural networks based on PAH molecular structure to predict their anharmonic spectrum You will test the accuracy of topological
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anharmonic DFT calculations of PAHs available in the team You will implement neural networks based on PAH molecular structure to predict their anharmonic spectrum You will test the accuracy of topological
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based on pathology or dysregulated cell biology. WP1. To generate well-defined iPSC and differentiate into neural cells that can be used for FTD and PD(D)/DLB subtype-tailored compound testing. WP2
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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), latch-ups, and the total ionising dose on spiking neural network performance. develop and test fault mitigation strategies, such as spike-based redundancy, reconfigurable neural routing, noise-aware