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for analysis of health record data for patient diagnosis and outcome prediction. Perform large-scale querying and analysis of clinical health record databases. Engage with clinical collaborators, to place the
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functional genomics, human genetics, and in vivo experimental systems to understand enhancer function across regulatory and phenotypic scales. We develop and apply both experimental and computational
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a highly dynamic multidisciplinary and collaborative environment. The new postdoctoral fellow will join a large team, currently twenty members, which is led by three faculty members and three senior
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for analysis of epidemiological data and large scale ‘omics data such as epigenomics, transcriptomics, miRNA, metabolomics, epigenetic aging. Analyzes data and writes interpretative reports. Verifies
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, and/or GATK with large-scale human genomic or other omics (preferably related to neurodegeneration) studies. Preferred Qualifications: Experience performing colocalization, Mendelian randomization
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for analysis of health record data for patient diagnosis and outcome prediction. Perform large-scale querying and analysis of clinical health record databases. Engage with clinical collaborators, to place the
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. Candidates must be comfortable practicing and/or learning high-performance computing for large-scale observational seismology on local and cloud UNIX environments. Desirable additional areas of expertise
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of the appointment. Demonstrated experience with deep learning methods or sophisticated mathematical frameworks applied to large-scale or scientific datasets. Experience working with observational seismology data (e.g
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projects. Fellows may pursue projects that utilize the CIP archive of large-scale social media data, as well as design and execute new data collection efforts that utilize existing research infrastructure
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accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly detection on graphs