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, with research expertise in geospatial AI, deep learning foundation models, hydrology, river science. Candidates will need to have completed their Ph.D. or have it completed by the start of employment
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a PhD candidate, you will: - Develop and train deep-learning
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evaluate deep learning models for MRD detection and characterization Collaborate with multidisciplinary teams across Dana-Farber Cancer Institute, the Broad Institute, and more Mentor and guide junior staff
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 6 hours ago
expose the successful candidate to cutting-edge genome editor engineering approaches and the delivery of these reagents in vivo via AAV or lipid nanoparticles. The successful candidate will also learn
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. They will learn to design interpretable, legally robust AI systems, including attention-based deep learning models and reinforcement learning approaches that adapt lineup presentation in real time based
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and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis
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twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL
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team players and passionate on cutting edge computer vision and machine learning technologies, as well as possess deep understanding of machine learning technology and experience on turning machine
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of deep neural networks in the field of adaptive processing of graph data (Deep Graph Learning) . The developed novel approaches will be applied to case studies in bioinformatics Requirements Additional