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metazoans by combining deep learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability
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, biology, and epidemiology, developing and applying novel statistical methods and deep learning approaches for global health challenges. The group’s research spans disease modelling, genomic analysis
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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-time Video Generation, digital double, human-like avatars. Profile PhD in Computer Vision Background in CS Research experience in gen AI, deep learning Strong computational and analytical skills, as
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Instructions Application through http://jobbnorge.no : https://www.jobbnorge.no/en/available-jobs/job/302170/up-to-5-phd-fellows-in-machine-learning-at-the-arctic-institute-for-ai-in-science-and-innovation
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, quantitative imaging, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector
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expected to have: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as
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Primary supervisor David Dowe Co-supervisors Ron Firestein Research area Machine Learning The proposed PhD project aims to build a machine learning/deep learning-based decision support system that
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Primary supervisor David Dowe Co-supervisors Ron Firestein Research area Machine Learning The proposed PhD project aims to build a machine learning/deep learning-based decision support system that