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Field
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in
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deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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redundancy in brain signals elicited by acoustic stimuli. The PhD project falls under Research Track 1: Informational Modes of Learning. Functional connectivity captures the statistical relationships between
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heating and cooling, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting