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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
(graph neural networks and transformers) The objective is to learn conformational heterogeneity directly from molecular dynamics simulations and to identify and predict allosteric communication pathways
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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source and made available to researchers, for example to calibrate the hyperparameters of a neural network. Definition of research activities and tasks to be accomplished: To meet these challenges, we
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Training and deployment of Spiking Neural Networks And will allow you to develop competences in Tactile Perception Spiking Neural Networks ESSENTIAL REQUIREMENTS To be registered as a student in an
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-informed neural networks (PINNs) and potentially generative adversarial networks (Pi-GANs). These models aim to predict cell fate and tumor development in CRC. The postdoc will collaborate with both
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within the EU-funded MINDnet Doctoral Network. The selected candidate will be enrolled as a supernumerary student in the PhD Programme in Artificial Intelligence at the University of Pisa (following a
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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within a Research Infrastructure? No Offer Description Work Plan Study and application of methods for extracting understandable concepts and inducing logic-based theories from neural networks. Study of
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: Artificial intelligence applied to seismics, neural networks, machine learning, synthetic data generation, seismic inversion, geological CO2 storage. Abstract: This research project aims to develop a synthetic
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Conference on Neural Networks (IJCNN), pages 1–10, July 2022. doi: 10.1109/IJCNN55064. 2022.9892277. URL https://ieeexplore.ieee.org/document/9892277/?arnumber= 9892277. G. Bellec, D. Salaj, A. Subramoney, R