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management and coding, machine learning AI, and familiarity with LSST data management image reduction and analysis tools. Familiarity with processing data at the DOE US Data Facility at SLAC National
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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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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
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collaboration with theorists, machine learning experts, and other experimentalists. Essential Duties and Responsibilities: Single crystal growth of quantum materials Performing transport and electron microscopy
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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