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Deep Learning based Controllable Animation Department of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Zhixiang Chen, Prof Jungong Han Application Deadline: 14 June
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]. For these reasons, we aim to go beyond the weaknesses of these methods, by investigating novel classes of generative models with deep learning to address anomaly detection. The goal of this PhD thesis is to explore
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Closing date: 23 June 2024 Campus: School of Mathematics and Statistics at the Camperdown Campus, The University of Sydney Position: Postdoctoral Research Associate in Deep Learning Theory
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18 May 2024 Job Information Organisation/Company Università degli Studi di Ferrara Research Field Mathematics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Country Italy Application Deadline 1 Jun 2024 - 23:59...
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for lithium-ion battery cells and fuel cells. Within the scope of your thesis, you will investigate deep learning-based defect detection approaches. To this end, we use roll-to-roll processes for the efficient
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based on deep learning techniques capable of analyzing different types of multimodal data. You want to be able to simulate data from different sources, e.g. RGB, Lidar or radar data, or analyze different
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in the center of Paris. He/She will integrate the MLIA team (Machine Learning and Deep Learning for Information Access) at ISIR (Institut des Systèmes Intelligents et de Robotique). MLIA is
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populations in outdoor environments. The study will primarily focus on developing deep learning-based audio analysis methods to count distinct bird calls in complex and noisy outdoor soundscapes. These calls
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4 May 2024 Job Information Organisation/Company Università degli Studi Padova Research Field Medical sciences » Medicine Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Country Italy Application Deadline 20 May 2024 -...
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team of machine learning scientists, MR scientists (Prof. SK Piechnik) and cardiologists (Prof. VM Ferreira). Recent deep learning breakthroughs have provided a new perspective to rethink contrast