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Field
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Are you interested in challenging deep learning at its core? And specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision
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The University of Exeter has a number of fully funded EPSRC (Engineering and Physical Sciences Research Council ) Doctoral Landscape Award (EPSRC DLA) studentships for 2026/27 entry. Students will be given sector-leading training and development with outstanding facilities and resources. The...
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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no
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with deep learning and 3D point clouds Apply for this job See advertisement About the position The Faculty of Environmental Sciences and Natural Resources Management (MINA) at Norwegian University
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representations. In this project, you will substantially improve quantitative magnetic resonance imaging (MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers
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(MRI) image quality using deep learning approaches. Quantitative MRI allows healthcare providers to quantitatively assess and characterize the state of a tumour and its microenvironment. This information
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experience in common deep learning frameworks (e.g., PyTorch and TensorFlow) would be a benefit; The qualities to carry out independent research, demonstrated e.g., by the grades obtained in your (under
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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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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strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain