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for observational studies Experience with machine learning techniques for patient-level prediction Prior experience working in distributed or federated data networks Familiarity with open-source research ecosystems
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to sustain an active research and publication agenda and to teach in the departmental undergraduate and graduate programs. Candidates with expertise in machine learning, big data, mathematical finance and
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. The interests of LABS are to develop and apply statistical, machine learning, and artificial intelligence (AI/ML) methodologies to "big data" in multi-omics and medical data for aging and diseases, such as
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information from clinical notes ? Implementing machine learning models for prediction and classification tasks in cardiovascular populations ? Cleaning, preparing, and managing large healthcare datasets
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for their stakeholders and society at large through our MBA, MS, PhD, and Executive Education programs. We are equally committed to cultivating new scholars and teachers and to creating and disseminating pathbreaking
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, coordination, and management of information and data, development and implementation of computer models and simulations, development of research materials (figures, presentations, papers, etc.) and work