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Field
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of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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statistical and deep learning-based methods; * Construct AI-driven models for mosquito habitat mapping, integrating diverse climate change scenarios to enhance predictive accuracy and future forecasting
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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 1 hour ago
designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology. Description: Exploration to deep space will require unprecedented
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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modelling are essential. Experience with healthcare data, algorithmic fairness, or deep learning for biomedical data will be advantageous. The successful candidate will contribute to high-impact publications
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of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow based generative
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learning, particularly in deep learning or related areas. No prior knowledge of cryptography is required. Expertise in optimization or efficient algorithm design will be considered an asset. Applications
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of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders
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tools capable of integrating, modeling and interpreting this wealth of information. It is in this context that artificial intelligence (AI) approaches, particularly deep learning, offer considerable