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Field
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
, Competencies, and Experience Strong research background in computer vision and multimodal machine learning. Experience with deep learning and multimodal/vision-language models. Strong programming and research
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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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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Postdoctoral Associate Cornell Lab of Ornithology College of Agriculture & Life Sciences Cornell University Ithaca NY The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose
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, computer vision, robotics, biomedical engineering, computer science, biomechanics, neuroscience, signal processing, or a closely related discipline. Strong expertise in machine learning and deep learning
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conduct research related to creating or testing deep learning models for genomics, exploring new techniques related to spatial simulations, or other topics discussed with the PI. Basic Qualifications Core