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very large datasets of epidemic indicators, such as case surveillance data, cellular phone data, and mobility patterns. Qualifications: PhD in a quantitative field such as mathematics, network science
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understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, particularly by leveraging large language and vision
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communication skills, and can work both independently and as an effective member of a large research team. The candidate will be expected to initiate new research proposals for both intramural and extramural
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, Division of Computational Biology) on research using large-scale EHR data sources, including Epic Cosmos and PEDSnet. Ideal candidates will have experience in one or more of the following areas: EHR-based
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experiments within the Pediatric Brain Tumor Research Program. This position will be responsible for evaluation and analyzing large sequencing and multiome data-sets. Baylor College of Medicine typically
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integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: UNMC is an Equal Employment Opportunity Employer, including an equal opportunity employer of protected veterans and individuals
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and social data. Minimum Requirements: A PhD degree is required. Preferred Qualifications: Experience with large-scale or high-dimensional datasets (e.g., cohort, registry, or omics data) Familiarity
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 28 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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performing experiments, analyzing data, contributing to manuscript and grant preparation, and mentoring and training laboratory personnel. Additional training and professional development opportunities aligned