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to develop 2D and 3D NMJ models for DM1, consisting of different combinations of patient-induced pluripotent stem cell (hiPSC)-derived neuronal and muscle cells, allowing the dissection of pathological
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spaceborne remote sensing. You will first identify large-scale drivers of compound extremes in models and observations, then build an emulator using advanced AI methods, such as convolutional neural networks
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programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning. In particular, you will be part of the Causality team under the supervision
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is embedded in an international academic–industrial collaboration and targets fundamental questions in end-to-end autonomous driving and neural view synthesis. Your work is expected to lead to