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position focuses on advancing the integration of gene regulatory network (GRN) simulations into multicellular and tissue-level systems using machine learning—particularly graph neural networks (GNNs) and
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on advancing the integration of gene regulatory network (GRN) simulations into multicellular and tissue-level systems using machine learning—particularly graph neural networks (GNNs) and reinforcement learning
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. The projects may also include to tackle benchmarking problems such as SAT, image processing, graph theories, boson/fermion sampling by applying classical machine/deep learning, neural network techniques and
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