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, or other relevant analytical software. • Knowledgeable of Bayesian statistical methods, numerical modeling methods, and other complex quantitative analytical methods. • Experience with open science practices
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the team’s work across its different content areas. We are seeking a candidate with strong quantitative and statistical modeling skills, particularly in Bayesian methods, who is ready to advance their career
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Department. This position will develop and evaluate techniques to infer properties of the ocean seafloor and water column from acoustic data. This involves theoretical development incorporating both
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conducting statistical modeling. The RS4 will work closely with faculty that have expertise in causal inference using observational data so will employ these methods in the statistical modeling work
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with large tech AI companies, Pharma AI/IT groups, and Academic collaborators. Build and optimize scalable training and inference pipelines for structured and unstructured biomedical data. Collaborate
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required for the proposed work, including causal inference and relative risk analyses. We are seeking an experienced and motivated Research Scientist to contribute to an innovative global health project