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of Novel Deep Learning Architectures for Fine Motor Test Analysis" Supervisor: Tenured Associate Professor Sven Nõmm Abstract This research initiative focuses on digitizing and analyzing fine motor tests
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Skip to main content. Profile Sign Out View More Jobs PhD scholarship in Uncertainty Quantification for Deep Learning - DTU Compute Kgs. Lyngby, Denmark Job Description Do you want to do research
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diverse cultural backgrounds to study the relationship between perceptual and cognitive aspects of colour communication. This involves using state-of-the-art multi-modal deep learning models to estimate
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efficiency of deep neural networks. Investigate the mathematical underpinnings of sparsity in deep learning and its effects on learning dynamics, and generalization. Implement and benchmark sparse training
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Aix Marseille University, Interdisciplinary Center of Nanoscience of Marseille (CINaM) | Marseille, Provence Alpes Cote d Azur | France | 3 months ago
Is the job funded through the EU Research Framework Programme? Not funded by an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD fellowship
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. To make deep learning algorithms efficient in real life it is important to combine software and hardware optimization when creating new deep learning algorithms. During the PhD we plan to propose novel
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The recent advent of deep learning (DL) has enabled data-driven models, paving the way for the full exploitation of rich image datasets from which physics can be learnt. Here at the University
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, this requires a multiple approach combining computational thermodynamics and deep learning. This PhD project will lead to the conception of functionally graded advanced components combining properties
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within a Research Infrastructure? No Offer Description Contexte et atouts du poste The main goal of this PhD project is to develope a deep learning framework for the design of cyclic peptides. This project
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to staff position within a Research Infrastructure? No Offer Description The vacancy is focused on calibration in deep learning. Deep Neural Networks (DNNs) have demonstrated significant predictive