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-evaluation and participates in Peer Review and Quality Assurance. Provides health education for acute and chronic medical conditions in a self-care model as well as wellness prevention model to patients and
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with AI and Physics (LEAP), an NSF-funded Science and Technology Center at Columbia University. Responsibilities will include: Analyze data from observations and model simulations of extreme MHWs. Apply
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. We use a combination of cutting-edge technologies, including comprehensive genomics and computational biology, genetic and transplantation-based cancer models, and real-time in vitro and in vivo
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with numerical modeling. If required, the assistant may aid in the hardware development for the new electromagnetic coils. Responsibilities (70%) Perform numerical optimization to obtain new (signs
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score and other comorbidity adjustment methods, latent variable analyses, advanced regression techniques including multilevel modeling and survival methods. The candidate will also interpret study results
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, clinical patient data mining, and to develop prediction models to optimize care and practice. Responsibilities Perform cost-effectiveness analyses and clinical patient data mining Develop prediction models
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provides a progressive, patient-oriented model of care coupled with innovative specialty care in one of the nation’s highest-ranking medical schools and hospital systems. Sponsored by leadership at Columbia
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. The successful candidate will contribute to the development of computational models that describe interfacial reactions in electrochemical systems. Reactions at electrode?electrolyte interfaces and the resulting
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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
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cancer. This job will be to perform preclinical studies with a range of therapeutic modalities, oversee multiple mouse models of gastroesophageal cancer, generate and culture gastroesophageal cancer