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learning to scale up the analysis of satellite imagery for climate-relevant applications. The role will consist of applying deep learning models to train image and text encoders that can be used
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developing and optimizing machine learning models, including deep learning models. 6. Deployment Knowledge: Familiarity with deploying AI models in cloud environments or on edge devices. 7. Problem
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the collection, interpretation, analysis, and documentation of data on prospective foundation donors and develop deep subject matter expertise and leadership in multiple areas of foundation research. The Prospect
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requires a Bachelor’s degree in biomedical engineering, computer science, electrical engineering or comparable field of study. Master’s and PhD level will also be considered. Proficiency in Deep Learning and
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competitive compensation, benefits, and a nurturing work atmosphere that unites passion and purpose. Learn more about us: https://dhip.dukehealth.org/about-us JOB LOCATION DHIP Administrative Offices RTP - 4825
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competitive compensation, benefits, and a nurturing work atmosphere that unites passion and purpose. Learn more about us: https://dhip.dukehealth.org/about-us JOB LOCATION DHIP Administrative Offices RTP - 4825
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technical experience in various areas related to machine learning, deep learning, clinical pathology, medical image analysis, etc. The initial appointment will be for 1 year, full-time, with opportunities
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standards in accordance with federal and state agencies and The Joint Commission (TJC) standards including National Patient Safety Goals Support and encourage voluntary submission of patient safety learning
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provides leadership in the organization. Goals of APP Transplant fellowship : Acquire a deep and broad knowledge base of the common disease processes for which patients are hospitalized, understanding
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complexity. 9. Maintain a deep understanding of multiple technologies, reference architectures, and business applications. 10. Experience in launching enterprise cloud-hosted platforms. 11