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data (Fondation Rothschild Hospital / INCC). The student will work at the intersection of artificial intelligence and cognitive neuroscience. The neural mechanisms of human language remain unknown
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related fields. Prior lab experience is preferred but not required. Candidates with research experience in machine learning and artificial neural networks, are strongly encouraged to apply. The candidate
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inference with deep-learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum, the deadliest malaria parasite species (read [1] to learn more about the ideas
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dynamic linear models (a type of state space model) Neural network-based time series models, specifically transformers Convolutional neural networks, for encoding video frames Closed frontier large
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, neuromechanical simulations or robots driven by connectome-constrained artificial neural networks. Candidates from outside the field of neuroscience are encouraged to apply, but must be curious, persistent, and
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extensive use of (deep) artificial neural networks reached most of the areas of society and technology. However, the theoretical understanding of their properties (and also possible limits) is
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-3373.e4. doi:10.1016/j.celrep.2019.11.017 Yu H., Samuels D., Zhao Y., Guo Y., Architectures and accuracy of artificial neural network for disease classification from omics data. BMC Genomics. 2019
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-3373.e4. doi:10.1016/j.celrep.2019.11.017 Yu H., Samuels D., Zhao Y., Guo Y., Architectures and accuracy of artificial neural network for disease classification from omics data. BMC Genomics. 2019
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but could become disruptive in the future. The team operates to high academic standards, publishes in peer-reviewed journals and conferences, and has built a broad European and international network
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physics, and artificial intelligence. Its goal is to implement neural-network operations directly in a physical optical system. The successful candidate will participate in the design and experimental