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with neuroimaging and neural signal processing tools, including fMRI, structural MRI, diffusion MRI, EEG, or related modalities. Strong publication record in AI, machine learning, computational
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Department with significant expertise in Machine Learning/AI are available to help provide overall guidance and strategy to the postdoc. Stanford Departments and Centers: Anesthesiology, Perioperative and Pain
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Qualifications: PhD in a relevant field is required; relevant fields include but are not limited to epidemiology, statistics, biostatistics, machine learning, data science, or other quantitative fields. Required
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, inferential and spatial analysis, as well as integrating machine learning techniques, and leading and drafting manuscripts. We will support and encourage the candidate’s independent research interests
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applications, and ability to quickly learn and master various computer programs. Must be technically rigorous, organized, and have demonstrated excellence, innovation, and productivity in research. Ability
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the evolution. Our project will contribute to the development of novel algorithms, especially in the field of machine learning. Position details Position title: assistant professor (postdoctoral position
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Ability to establish and maintain a vigorous, extramurally funded, research program in artificial intelligence and machine learning applied to the physical sciences Evidence of peer-reviewed publications in
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care for patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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and inverse reinforcement learning. Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer vision; machine intelligence; explainable AI; cognitive/brain
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a unique opportunity to work in a cutting-edge, interdisciplinary environment, leveraging a novel in-vitro model of the human uterus and/or cutting edges machine learning techniques to make