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, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in
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neurostimulation (TMS, tDCS, etc.), neuroimaging (EEG, MRI, MEG, etc.), or multi-modal neurostimulation-neuroimaging techniques. Machine learning background and/or knowledge. Experience working with individuals with
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the completion of their research projects, fellows in the Smith lab have the opportunity to work one on one with the PhD biostatistician associated with our laboratory to learn introductory machine learning
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record, and available funding. Education Requirement: A PhD degree (or about to complete) in machine learning, or a closely related field, is required. Required Qualifications: Practical experience in