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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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2026 Interviews: TBC (online) Start date: September 2026 Project Title: AI-Enhanced Battery State of Health Estimation Using Ring Probabilistic Logic Neural Networks Director of Studies: Prof Shahab
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. Indeed, the methods currently used rely on optical image databases of various avalanche observations. A deep neural network was trained on this data to enable automatic avalanche detection FIGURE 1 (a) [1
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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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) relationship with the low-fidelity response. Extensions include nonlinear information fusion with GPs, Bayesian multi-fidelity inference and deep probabilistic surrogates, as well as MF neural networks
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basic technologies, computer vision, image understanding, and other multi-media sensing and recognition techniques are widely studied. In addition, machine learning including deep neural networks
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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 21 days 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
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have become a major challenge for understanding, recording, and modulating neuronal network activity, ranging from in vitro cellular models to implantable neurotechnological applications. In the long
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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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: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