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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 14 hours ago
estimating treatment effects in the presence of intercurrent events whose occurrence may itself carry prognostic information. Methods of interest could include survivor average causal effect (SACE) estimators
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surgery. However, the growing use of TAVI has also increased the need for accurate methods to assess valve disease, identify patients who will benefit from intervention, determine the optimal timing
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 14 hours ago
just medicines. Research Project: Under the guidance of a mentor, you will implement two-stage meta-analytic models and weighted least squares correlation methods to estimate the surrogacy strength
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: Strong experience with flow cytometry, murine experiments, ELISA, and bacterial culture methods Some experience with microbiome methods and an interest in spatial transcriptomics Demonstrated skills in
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Respiratory Viruses Division (CORVD), National Center for Immunization and Respiratory Diseases (NCIRD), CDC. You will receive training in advanced molecular methods, next-generation sequencing (NGS), viral
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aerial vehicle (UAV) imagery collection and processing, deep learning methods, and rangeland vegetation communities in Oregon and Idaho as part of an interdisciplinary team including researchers in plant
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affiliated with Columbia University. Duties and Responsibilities: Construct air pollution and meteorological data prediction models using machine-learning based methods Conduct epidemiologic analyses studying
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relaxation, and elevated filling pressures—cannot be measured directly using current non-invasive methods. This project aims to improve the assessment of diastolic function by combining echocardiographic
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, and environmental factors associated with diabetes incidence, prevalence, complications, and trends. Learn and apply advanced statistical and machine learning methods, including cluster analysis and
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environmental factors associated with CKD incidence and trends. Apply advanced statistical and machine learning methods, including semi-supervised cluster analysis, to characterize populations with diabetes and