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-aware AI under practical deployment constraints. Familiarity with efficient neural network architectures, including alternative attention mechanisms or mixture-of-experts models. Exposure to trustworthy
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; 2.) use invasive and non-invasive brain stimulation to probe the causal relationship between neural network dynamics and behaviour; 3) leverage these insights to pioneer closed-loop approaches
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; use invasive and non-invasive brain stimulation to probe the causal relationship between neural network dynamics and behaviour; leverage these insights to pioneer closed-loop approaches to therapeutic
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neural network has reduced this cost by a factor of 5000 (Radureau, 2025). This project aims to develop a mesoscopic radiative model to overcome the CFL constraint by adapting the average photon speed
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the foundational mathematics and programming skills necessary for creating basic neural networks and deep learning models from the ground up. Additionally, it is designed for those keen on comprehending
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optimization. At the same time, AI models, especially deep neural networks, are becoming increasingly complex, with energy consumption and carbon footprint emerging as major concerns. For instance, training a
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passe pas à l'échelle et induit des latences de signalisation incompatibles avec la dynamique satellite [5–6]. Alternatives décentralisées via réseaux de neurones de graphes (Graph Neural Networks, GNN)[8
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,” Machines, vol. 9, no. 10, p. 210, Sep. 2021. https://doi.org/10.3390/machines9100210 [3] L. Podina, M. Torabi Rad, and M. Kohandel, “Conformalized Physics-Informed Neural Networks,” arXiv preprint arXiv
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Description The overall objective is to improve the integration of polar ice sheets into Earth system models by using neural network emulators at the interface between an Antarctic ice sheet model (Elmer/Ice
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | about 1 month ago
Academy of Sciences (OeAW), Austria’s leading non-university research and science institution, is offering a Position as Praedoc (Diss) (f/m/x) in Mathematics of Neural Networks and Neural Operators part