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Field
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)-statistics, (applied) mathematics, or a related STEM field. Prior working experience with EHR data, machine learning, NLP, bioinformatics, and large language models (LLM) is preferred. In particular
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, high-performance computing (HPC), dimensionality reduction, and machine learning. Your responsibilities will include publishing research in leading conferences and journals, contributing to grant
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community health workers (CHWs) with advanced data-driven tools to improve healthcare access and outcomes for high-risk patients. The postdoctoral researcher will play a key role in translating machine
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Computer Science, Electrical/Computer Engineering, AI/ML, or a closely related field. Demonstrated experience in AI/ML model development, LLM tuning, generative AI, functional safety and risk analysis. Proficiency
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. Strong technical foundation in statistical modeling, machine learning, or AI; Proficiency in computing and programming; excellent communication and collaborative skills. A record of strong publications in
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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campus in Lemont, Illinois five days per week. Preferred Qualifications Proficiency in programming (e.g., Python) for advanced data analysis, machine learning, and computer vision to accelerate insights
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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well as bulk RNA-Seq, Proteomics, and Metabolomics generated from mouse and patient cohorts with rich clinical data - Advanced modeling of arrhythmias using generalized linear models and machine learning
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how