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responsibilities will span all stages of research, including collecting data of in both tabular and spatial formats, developing algorithms that clean and organize data, conducting statistical analyses, running
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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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research activities, assists in preparing human subjects protocols, manages and analyzes data across multiple projects. Contributes to building traditional statistical models and machine learning algorithms
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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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of common healthcare related coding systems (ICD9/10, CPT, LOINC, RxNORM). Advanced knowledge of machine learning techniques and algorithms. Experience developing, debugging and testing reproducible and
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algorithmic transparency and accountability. AI as a tool for libraries: Assess AI tools that could benefit the Library’s own operation and services and undertake research into use of AI for library and
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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