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Università degli studi di Roma Tor Vergata Dipartimento di Biomedicina e Prevenzione | Italy | 3 days ago
supervisor’s guidance. Activities will include implementing simulation environments based on neural dynamics models, spiking neural networks and reservoir computing, and comparing closed-loop control strategies
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Università degli studi di Roma Tor Vergata Dipartimento di Biomedicina e Prevenzione | Italy | 3 days ago
supervisor’s guidance. Activities will include preprocessing and integrating available neuroimaging data and electrophysiological signals, learning shared representations, and comparison with dynamical models
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mechanics, information theory, stochastic processes, population dynamics, and neural networks. Within this framework, machine learning systems and artificial generative models will also be considered, where
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) and CosmoStat at CEA Paris-Saclay, with a view to developing cosmological inference methods based on forward modelling for the analysis of the LSST survey from the Vera C. Rubin Observatory. To exploit
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-based policymaking. Research The successful candidate will conduct research within ARC-Air, focusing on the integration of satellite observations, atmospheric models, and ground-based measurements
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Join the School of Engineering Mathematics and Technology at the University of Bristol as a Postdoctoral Research Associate in genome-scale metabolic modelling for red blood cell engineering. This
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Intelligence, Remote Sensing, and Geospatial Data Science. The successful candidate will contribute to the development of intelligent models that learn from large-scale and heterogeneous geospatial data and
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The role Join the School of Engineering Mathematics and Technology at the University of Bristol as a Postdoctoral Research Associate in genome-scale metabolic modelling for red blood cell
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lncRNAs in transgenic pigs as models for xenotransplantation. Where to apply Website https://selezionionline.cnr.it/ Requirements Additional Information Eligibility criteria Eligible destination country/ies
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these structures and models through data collection and statistical analysis Where to apply Website https://pica.cineca.it Requirements Additional Information Eligibility criteria Eligible destination country/ies