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programming skills in modern languages such as Python or C++. Experience in statistical analysis, machine learning, and data-driven modeling applied to large astronomical datasets and time-domain surveys is
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required; Significant experience in molecular biology and animal models of epilepsy preferred. Requires successful completion of a background check. Selected candidate may be requested to complete a pre
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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: Minimum Required Qualifications PhD in Statistics, Engineering, or related discipline with experience developing or using image processing and segmentation software and AI models. Experience coding in
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preclinical models and will have the opportunity to develop and refine novel systems. Our laboratory is well-resourced to conduct these studies. It has access to human biospecimens to confirm the relevance
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QUALIFICATIONS AND EDUCATION: Skillful with cryo-EM data processing and structural refinement software (e.g., cryoSPARC, RELION, Phenix, Coot). Expertise in computational modeling and structure-based protein
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for science and discovery. The ideal candidate should also have at least 1 first-authored publication in press, and have experience working with murine models in a laboratory setting. Minimum education
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, and metabolic disorders. Experimental approaches include genetically engineered mouse models, MI and sepsis (CLP/LPS) models, aging and metabolic disease models, and molecular, cellular, imaging, and
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roles of pathogenic and protective roles of novel B cell subsets in multiple sclerosis and animal models of multiple sclerosis, as well as the impact of biological aging on the pathogenesis and clinical
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data analysis (e.g., MRI preprocessing, statistical modeling, familiarity with tools such as FSL, SPM, AFNI, or similar platforms). Proficiency in statistical programming (e.g., R, Python, MATLAB