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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
these architectures through simulation (e.g. ns-3) and hardware test platforms (e.g. Software Defined Radio) will enable critical information for architecture selection of future planetary missions. Field of Science
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practical experience with qualitative research methods, particularly discourse or content analysis. You are familiar with Qualitative Data Analysis (QDA) software like Nvivo, MaxQDA or Atlas.ti. Interest in
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simulation software to study interactions. Applicants must demonstrate a track record in applying such approaches including a relevant Ph.D./DPhil and experience. Applicants must also be confident in using
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-Society. The division is home to several large software projects and datasets that help to disseminate this research to the industry and public. Technology for people DTU develops technology for people
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points in the first phase will be invited to an interview. The interview may be given in either Spanish or English (as chosen by the candidate) and take place using internet communication software (Zoom
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the first phase will be invited to an interview. The interview may be given in either Spanish or English (as chosen by the candidate) and take place using internet communication software (Zoom) that allows
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; Experience with acquisition of large datasets such as (but not necessarily restricted to) genomic/genetic data and related bioinformatics pipelines/phylogenetic software; and Demonstrated experience in
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, user-friendly software tools for the community. Publish results in top peer-reviewed journals and conferences. Qualifications Required: Ph.D. (obtained or expected) in a quantitative discipline: Computer
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machine learning software tools and frameworks Implementation of scalable numerical algorithms on HPC architectures Excellent written and verbal communication and interpersonal skills. The ability to obtain
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: Experience in one more of the following areas: Mathematical methods for kinetic and/or fluid equations Multiscale problems and model reduction Modern machine learning software tools and frameworks