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. Work with stakeholders to implement corrective actions, best practices, and lessons learned into existing processes. Flow down requirements from codes, standards, Federal Regulations, and contract
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, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
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through multidisciplinary research, data analytics, modeling, engineering design, decision support, and visualization. The group develops innovative tools and technologies to enhance the efficiency
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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, and data science and analytics. Preferred Qualifications: Experience leading teams and performing research in artificial intelligence / machine learning, specifically for cybersecurity, signal
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service offerings (e.g., large-scale geospatial compute pipelines, data ingest/curation/archive, analytics/visualization, user support). Establish operating policies, SLAs, user workflows, resource
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portfolio includes materials science and engineering, chemistry, geoscience, nanoscience, soft matter science, analytical chemistry, and nuclear and particle physics applied to a broad range of scientific and
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information. Effective written and verbal communication skills. Analytical mindset with interest in workforce data and reporting. Ability to manage multiple priorities in a structured, deadline-driven
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of quality initiatives, assesses satisfaction, and exchanges feedback and lessons learned. Analyze, interpret, and communicate quality and performance data to management in support of established metrics and
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, and compliance requirements. Strong aptitude for computer systems, electronic tools, and digital workflows. Ability to learn and adapt to new technologies, including AI-enabled tools used to support