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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
programming (MATLAB, C++, Python, R, etc.) • Experience with MR physics and/or pulse sequence programming (Siemens or Bruker platforms) is preferred but not required • Experience with machine learning
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targeted ultrasound delivery, advanced neuroimaging, and closed-loop control. The primary objective of this postdoctoral/PhD project is to advance the chemical formulation and engineering of ultrasound
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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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author publications. Great writing skills, motivated and driven to publish. Additional Qualifications: Background in bioinformatics systems, connectomics network analysis and machine learning modeling
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routine background checks. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms
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computer science using data-driven techniques (graph theory, ICA, machine learning), in other imaging modalities (DTI; MEG), and in multimodal integration will be relevant. Experience with AFNI/SUMA, SPM, FSL
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contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and clear written and verbal communication
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of gerontology: https://gero.usc.edu( opens in new window) The Irimia Laboratory leverages neuroimaging, neurogenomics, and deep learning to study the aging brain in health and disease, particularly in
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of the Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine in Baltimore. The selected candidate will work on federally funded projects associated with neuroimaging