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Field
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natural language processing methods for analysis of unstructured clinical and biomedical data. 4. Experience with cloud-based and high-performance computing environments to support scalable data
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software (e.g., R or Python). Google Earth Engine and cloud-based geospatial analysis. Spatial visualization, mapping applications, and predictive ecological modeling. Applicants must possess a valid U.S
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, engineering, bioinformatics, computer science, mathematics, statistics, data mining, parallel programming, supercomputing, or cloud computing . Application Instructions How To Apply Interested individuals
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data and storage systems. Evaluation of cloud data storage and analysis solutions (e.g., key-value stores, object or document storage, graph analytics systems) deployed on HPC computational and storage
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deploying models to cloud environments (e.g. AWS) Experience with or strong interest in privacy-preserving ML or human subjects research Passionate about child health and development Required Application
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publications. Experience with long-read sequencing data, tumor-normal somatic variant analysis, or germline variant interpretation is strongly preferred. Familiarity with cloud-based analysis of controlled
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(HPC) and cloud-based computational resources, when appropriate. Performs multivariable regression, survival analysis, longitudinal analysis, correlation analysis, clustering, dimensionality reduction
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with generative AI agents applied to data analysis or visualization authoring. Scientific project management experience, including coordination of multi-partner research activities. Experience with cloud
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external parties, so methods must avoid external cloud APIs and be light enough to run on limited hardware. Your job This 24-month postdoctoral position is a close collaboration between the National Police
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datasets. Experience with cloud-based storage and service tools is helpful Preferred Qualifications: MS or PhD in a relevant field Experience with network neuroscience, graph theory, or connectomics