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computational approaches towards a new project which seeks to better understand the causes and consequences of the correlation between multiple traits and to quantify trait variation that arises from new
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ABOUT VINUNIVERSITY’S RESEARCHERS 200 VinUniversity is proud to launch the Researchers 200 Program, designed to attract exceptional early-career researchers from around the world to join our vibrant
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PhD in Computer Science: Sustainable AI for Plant Species Recognition in Tropical Forests School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Jefersson Alex dos
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application of computational tools for the early detection and deconstruction of chromosomal instability in cancer” For further information about the research group, including their most recent publications
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position initially and is expected to be held full time and in person. You will join the CNNP Lab, which is well supported with recent funding of over £3M. The lab is based in the School of Computing
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis
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samples. All computational methods and algorithms will be implemented as part of the python based MetaboLabPy platform (https://doi.org/10.3390/metabo15010048 , https://github.com/ludwigc/metabolabpy