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departments within the Biomedical Graduate Research Organization (BGRO) at Georgetown University Medical Center (GUMC). This position is responsible for processing employment requests and documents for faculty
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scientists and software engineers to ingest (ETL) structured and unstructured datasets into Google Cloud Platform, apply Natural Language Processing (NLP), Machine Learning (ML), predictive modeling, and other
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offices, regarding matters pertaining to the unit's finances and HCM. Duties include but are not limited to: The initiation and/or completion of a wide variety of HCM-related forms, or processes
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Language Processing (NLP), Machine Learning (ML), predictive modeling, and other advanced techniques to evaluate hypotheses and derive data-driven insights Communicating, in written and verbal formats, CSET’s data
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analysis; Ingesting structured and unstructured data sets into GCP, building and maintaining data processing pipelines, and delivering improvements to product code and documentation to increase analytic
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pathway programs. Manage and support core ODEIB/GEMS program administrative functions – to include general communications, application processes, and student support. Support the development, implementation
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are not kept on file for future positions. Need Assistance: If you are a qualified individual with a disability and need a reasonable accommodation for any part of the application and hiring process, please
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compliance processes is highly desirable. Work Mode Designation This position has been designated as On-Campus. Please note that work mode designations are regularly reviewed in order to meet the evolving
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qualified individual with a disability and need a reasonable accommodation for any part of the application and hiring process, please click here for more information, or contact the Office of Institutional
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qualified individual with a disability and need a reasonable accommodation for any part of the application and hiring process, please click here for more information, or contact the Office of Institutional