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). Contribute to image processing and algorithm development to support the identification of novel biomarkers and disease phenotypes. Write clean, efficient code primarily in Python and work with Bash/Slurm
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using supervised and unsupervised machine learning/deep learning techniques for various research applications. Design and implement NLP algorithms and techniques for text preprocessing, feature extraction
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with the goal of better understanding how places impact people. We develop machine-learning algorithms and non-linear measure of brain dynamics to quantify more vs. less effortful brain states. This is
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, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis. Collects, organizes, and may analyze information from the University's various internal data systems as well as from
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algorithms for clinical processes in the transplant program and more broadly in the Section of Pediatric Hematology/Oncology & Stem Cell Transplantation. Coordinates transplant research protocol development