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Field
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presently operates multiple large HPC systems ranging from a 120k x86 CPU core general purpose system to a system explicitly designed for Artificial Intelligence and Machine Learning, and a nationally
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Specialist to join our innovative team. The Research Data Management Specialist will: Manage multiple datasets and corresponding documentation, visualize data, and work closely with the analytic team
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phenotyping of health outcomes at multiple time-points. S/he will work within a diverse, highly collaborative, and multi-disciplinary research environment and interact with world leaders in the fields of cancer
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acquired at multiple resolutions (tissue-level, single-cell/nucleus, and spatial transcriptomic data), requiring complex integrative analyses. The successful candidate will lead the analysis of a large
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Engineering, or a related discipline. Proficiency in Java and/or Python programming. Familiarity with software development tools and platforms (e.g., IDEs, cloud environments etc). Demonstrated ability
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 3 hours ago
(https://airbornescience.nasa.gov/mms) has a long history of providing research-quality, in situ meteorological measurements on multiple platforms as part of over 30 airborne missions since the 1980s. We
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, or Python Proficiency with statistical analysis (descriptive, regression) Intermediate to advanced skills in Microsoft Excel with ability to expand skills as needed Experience with data cleaning, database
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implementation of new virtualization, storage and backup systems; Scripting to automate routine tasks preferably using Python and/or Powershell. Familiarity with: Management of Enterprise solutions including
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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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support applied research on Texas residential markets. The ideal candidate will have experience collecting and analyzing economic data, proficiency in statistical tools like R or Python, and the ability