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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 9 days ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0049-NPP-MAR26-LRC-EarthSci How to Apply All applications must be submitted in Zintellect Please visit the NASA
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distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints. Cross‑Paradigm Integration(new optional emphasis): Explore how
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maintain contributor guides and onboarding documentation to lower the barrier for external contributors. Support code review processes via GitHub Pull Requests following open development principles
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completion of all pre-employment or background checks required for the role in terms satisfactory to the University. Also, to meet the University’s obligations under the National Higher Education Code
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science methods application and dissemination Demonstrated proficiency through previous developed analytical codes with R Language for Statistical computing, and qualitative analysis using NVivo
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would have strong interpersonal skills, experience generating and analyzing stable isotopic data, intermediate R coding and data management skills. Expertise in isotope ratio mass spectrometry (IRMS
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would have strong interpersonal skills, experience generating and analyzing stable isotopic data, intermediate R coding and data management skills. Expertise in isotope ratio mass spectrometry (IRMS
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encourage you to apply, regardless of gender, disability and cultural background, or whether you have been out of work for a period of time. Salary and conditions As a Postdoctoral Fellow (code 1352) you are
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
and Environmental Engineering at the University of New Hampshire. The successful candidate will be responsible for developing and coding workflow processes and designing experiments for multisensory data
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). Proficiency in Python and experience with R/Seurat or Scanpy. Strong skills in writing efficient, reproducible, and well-documented code. Evidence of productivity through first-author publications or preprints