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Field
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longitudinal modeling, machine learning methods, subgroup analysis, or other advanced modeling techniques is highly desirable. Software Proficiency: Experience with neuroimaging tools such as AFNI, SPM, FSL
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for evaluation by the closing date of this announcement. Strong experience in using MRI to study brain structure. Extensive experience with machine learning in image analysis, particularly with MRI of the brain
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translational research involving multimodal neuroimaging analyses, statistics, machine learning, and/or glucose metabolism are preferred. Education and Experience Requirements: PhD in neuroscience
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. The appointee will primarily conduct research applying advanced machine learning/AI (including techniques like deep learning) to analyze complex biological and clinical data (e.g., single-cell multi-omics
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The X-ray Imaging Group (IMG) at the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in biomedical imaging and image processing to develop advanced processing
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will work on multiple projects funded by NIH/NHGRI. The objective of the position is to develop novel statistical methods and computer software and analyze large scale biological data from biobanks
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challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
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programming; experience in Python for machine learning and/or digital image processing is preferred. Strong communication skills, both in formal written reports/manuscripts and oral presentations. Language
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the pre- and post-processing of Magnetic Resonance (MR) images (or utilization of existing brain imaging markers), taking peripheral or central biomarkers, and regressing them against those images using
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modeling of crystals, dislocation dynamics, and defect analysis, linking atomic-scale simulations to macroscopic properties. Familiarity or interest in machine learning methods and computing frameworks