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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both
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of the Postdoctoral Research Associate includes contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will
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aspects of Cultural Heritage Science and the challenges inherent to this field (experimental noise, few-data regime) will have to deploy deep learning algorithms using Python/Keras/Pytorch or equivalent
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delineation and improve the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and
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Are you interested in cutting-edge research at the intersection of large language models, deep learning, and information retrieval? The Information Retrieval Lab (IRLab) at the University
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of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large
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Processing Skills required: - Medical computer programming: python, 3D slicer, LCmodel (optional), FSL, spm, ants) - Artificial Intelligence skills and deep learning experience - Proficiency in Tensorflow
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 16 hours ago
skills acquired in their doctoral programs or to learn new research techniques, in preparation for an academic or research career. In the process of further developing their own research skills, it is
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. Wildfire, climate change, and ecosystem management Our lab works at the intersection of theoretical and empirical science. We value applicants who combine strong quantitative skills with a deep interest in