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models (LLMs) in health data analytics. The position requires a demonstrated commitment to foster interdisciplinary collaboration with colleagues in public health, medicine, computer science, engineering
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doctorate (PhD or MD) in Health Informatics, Computer Science, Software Engineering, Information Science, Data Science, or other relevant STEM discipline with strong technical application development and R
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computer programming for health data analytics using Python and/or R, applications of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) in healthcare, health data
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analysis techniques * Collaborate with faculty in analysis of large datasets including combining and transforming data from platforms such as EPIC or CMS into analytical databases * Develop and implement
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underlying spatial data, high-dimensional and big data (e.g., data from wearable devices, electronic health records), Bayesian statistics, and learning algorithms as novel data analytical tools in applications