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system. For the meta-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine
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many opportunities to learn new and advanced state of the art techniques and strengthen their grant and fellowship application skills. In addition, the candidate will have a broad range of local and
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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) and bioinformatics tools Familiarity with data science, machine learning, artificial intelligence, natural language processing and applications to electronic health records and big data and
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seek a full-time postdoctoral researcher to work at Duke University on a project at the interface of neuroscience and machine learning. We seek to advance our understanding of neural systems and
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novel statistical methods motivated by medical research needs Solid background in causal inference and survival analysis Experience with clinical trial research, machine learning, and high-dimensional
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medical research needs Solid background in causal inference and survival analysis Experience with clinical trial research, machine learning, and high-dimensional statistics (desirable but not required
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, ChIP-seq, and ATAC-seq, CRISPR and RNAi perturbation screens 3. Ability to build predictive statistical and machine learning models that integrate multiple data types, including linear and nonlinear ML
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interested in applicants that have experience in one or more of the following areas: satellite remote sensing, energy balance modeling, and machine learning. In addition to scientific expertise, the successful