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on common medical imaging data augmentation techniques for robust model design. Strong written & oral communication skills including evidence of publishing peer reviewed research articles. Desirable criteria
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-cigarette nicotine vapor, augment model AAA. Exposure to tobacco smoke, nicotine, and vaping can cause cellular epigenetic alterations, which may be transmitted in a transgenerational fashion. Our data show
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
, Biomedical Informatics, Computer Science, or a related field. Required Qualifications, Competencies, and Experience Experience deploying and working with LLMs Agentic workflows and retrieval augmented
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) Development of an Augmented Smart Classroom for Personalized Learning (SmartClass) serving as a test-bed for the collection and analysis of students and professors data, leveraging on data analytics and machine
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imaging data augmentation techniques for robust model design. Strong written and oral communication skills including evidence of publishing peer reviewed research articles. Desirable criteria Experience
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libraries for developing deep learning models. Familiarity with medical image such as MRI, CT, or volumetric ultrasound. Knowledge on common medical imaging data augmentation techniques for robust model
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learning and data augmentation for soil and biomass carbon forecasts; developing a computational framework for data production in cooperation with Research Software Engineers; collaborating and coordinating
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augmentation for soil and biomass carbon forecasts and scenario modelling across Europe; developing and benchmarking uncertainty quantification methods for space-time predictions and for spatial blocks
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(LLMs), and Vision Language Models (VLMs) Develop Retrieval Augmented Generation (RAG) models Developing manifold learning (e.g., tSNE and UMAP), unsupervised clustering Analyze electronics health record
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(LLMs), and Vision Language Models (VLMs) Develop Retrieval Augmented Generation (RAG) models Develop manifold learning (e.g., tSNE and UMAP), unsupervised clustering Analyze electronics health record