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analysis, chemometrics, neural networks, classification or regression models); familiarity with large language models (LLMs) and other artificial intelligence techniques is valued; b) Experience in
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Reference Number BAP-2026-500 Is the Job related to staff position within a Research Infrastructure? No Offer Description Modern embedded AI systems rely on Deep Neural Networks (DNNs) running on resource
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representations, and flow matching) for uncertainty-aware 3D reconstruction of coronary anatomy from 2D X-ray angiography; develop physics-informed neural networks and graph-based neural operators for fast
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, and EHR data. Experience with modern deep learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, and SciPy. Familiarity with convolutional neural networks (CNNs), graph
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 2 months ago
fitted with sensors, we can also access precise physical measurements. Recent work in AI-for-Science has shown that neural-network-based meta-models can also assimilate measurements. Machine learning
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have a strong interest in graph-based learning (e.g., graph neural networks). You have experience with deep
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al., “Deep Transfer Learning for Fault Diagnosis”, IEEE Transactions on Industrial Electronics, 2020. • Zhang C. et al., “Graph Neural Networks for Power Systems”, Electric Power Systems Research, 2023
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Technologies (Ireland); and a network-wide training program. Responsibilities and qualifications The PhD scholarship is on the topic of “Carbon-Aware Neural Architecture Search (NAS)”. Most AI models are built
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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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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