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and neural science, and an interdepartmental neuroscience graduate program: http://neuroscience.med.utah.edu . Beyond the department, faculty benefit from extraordinary opportunities
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of compensating for nonlinear PA characteristics under dynamic operating conditions. Advanced machine learning and neural network approaches will be explored to improve linearization performance while reducing
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diverse set of time-dependent forecasting models (e.g., neural network, mechanistic, statistical, and data-driven) to serve as experts within the integrative architecture. (iii) Mixture-of-experts
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concentration/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical
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. For more information about the RNA Technologies Flagship, visit: https://rna.iit.it/ The project aims to develop a new generation of artificial intelligence models to systematically investigate the role
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Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 2 months ago
to the development and the analysis of modern machine learning methods, with a focus on probabilistic modelling that enables, for example, to account for uncertainties when training neural networks, to capture complex
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the funded line of research “Structural Neural Networks”. 1.2. Unit in charge of the line of research: Department of Computer Science and Artificial Intelligence. 1.3. The first project in which the successful
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approaches combining artificial intelligence tools (neural networks). The ideal candidate will show initiative, autonomy, rigor, curiosity, and a strong desire to learn, along with excellent writing and
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, host genetics, and addiction vulnerability. The postdoctoral fellow will lead the development of cutting-edge, explainable graph neural network (GNN) models that integrate microbiome functional profiles
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models