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Human-Centered Artificial Intelligence and the SLAC Machine Learning Program. KIPAC also has strong ties and active collaborations with theorists at LITP @ Stanford and SLAC. The positions offer a
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detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning, and development of algorithms for real-world clinical data. The fellow will have the
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the tool. Mentorship and Collaboration Dr. Philip Fisher will serve as the official faculty mentor for this fellowship. The fellow will also work closely with SCEC Senior Machine Learning Engineer Dr
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engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data; publications in medical imaging or health data science are highly
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on complementary approaches to T cell recognition. Our group provides an intellectually rich environment, with scientists applying genetics, proteomics and machine learning to better understand
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Applicable: Several other collaborators in the Anesthesiology Department with significant expertise in Machine Learning/AI are available to help provide overall guidance and strategy to the postdoc
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progress and training/career goals Appointment Start Date: Flexible start date Group or Departmental Website: https://clarkelab.stanford.edu/ (link is external) How to Submit Application Materials
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relevant field is required; relevant fields include but are not limited to epidemiology, statistics, biostatistics, machine learning, data science, or other quantitative fields. Required Application
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: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including functional MRI, structural MRI, connectivity, or brain circuit
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Silicon Valley, the Colman Lab utilizes state-of-the-art AI-assisted tools and innovative machine learning (ML/AI) methodologies to move the needle on translational medicine. The postdoctoral fellow will