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Field
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team to deliver innovative, reliable solutions that support ARL’s mission and strengthen the systems our customers depend on. ARL is an authorized DoD SkillBridge partner and welcomes all transitioning
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. Responsibilities include analysis, design, configuration, administration, testing, and ongoing support of web-based and cloud applications, including SaaS, collaboration, and identity management tools. The incumbent
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for external audiences. · Think critically about AI-generated content rather than accepting it at face value. · Are organized, reliable, and comfortable with structured tasks like data tracking and reporting
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platforms. • Experience with SQL for data transformation and analysis. • Familiarity with Epic Clarity or Caboodle data structures preferred. • Experience working in agile product delivery preferred.
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 12 hours ago
Infrastructure The Information Technology Department supports administrative systems, academic technologies, and research computing. System reliability and campus operations are strengthened through
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, reliability, and usability of institutional information. Conduct statistical, predictive, forecasting, and qualitative analyses of structured and unstructured institutional data, including survey responses and
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Postdoc (f/m/d) Mechanical Characterization and Materials Assessment for Nuclear Applications / P...
structural materials is an advantage # Experience in fractographic or microstructural characterization is an advantage # Familiarity with scientific data analysis environments # Sound knowledge of quantitative
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Siri Pedersen 18th October 2026 Languages English Norsk Bokmål English English PhD Fellowship in Public safety, Underground applications and Spatial analysis Apply for this job See advertisement
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/Experience areas include: Past success solving complex analytical or engineering problems, using structured methodologies to reach effective, defendable solutions Failure analysis, reliability engineering, or
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to the development of a multi-component framework for reliable and computationally efficient fatigue diagnosis and prognosis of steel structures. Building on the group's established expertise in virtual sensing and