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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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successful candidate, you will: This project with Dr. Nagarajan Vaidehi involves developing and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in
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The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model that can
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The role The Atmospheric Chemistry Research Group (ACRG) and School of Engineering Mathematics at the University of Bristol have developed GATES, a graph neural network (GNN) machine learning model
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at the intersection of machine learning, robotics, functional safety, and relevant machinery directives. In addition, the DC will contribute to the dissemination of project outcomes through digital and social media
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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application! We are now looking to appoint a postdoc in the field of AI and machine learning with a focus on scientific applications. Work assignments The primary focus of the postdoc positions is research in
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or further information feel free to contact us. Job description: - Application of specially developed approaches to define transferable force-fields with machine learning for different classes of complex