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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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Ine-Therese Pedersen 15th August 2025 Languages English Norsk Bokmål English English PhD position in Deep Learning for Metocean Data Apply for this job See advertisement About us We are announcing a
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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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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group has implemented state-of-the-art deep learning for underwater communications; deep learning models underwater environment based on real data. Our preliminary study shows that state-of-the-art deep
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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Deep learning has
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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