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in advanced machine learning algorithms. This position resides in the Manufacturing Systems Analytics (MSA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate
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is building agentic AI workflows that help discover, gather, validate, and standardize open-source data for downstream geospatial analytics and machine learning. The position offers a unique
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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in urban-scale building energy modeling, software development (esp. Python), or Artificial Intelligence/Machine Learning (AI/ML) Strong ideation, writing, and communication skills for establishing
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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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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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. 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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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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group in the Safety & Operations Support Division and will be matrixed to support the Nuclear Analytical Chemistry (NAC) Section, Chemicals Sciences Division (CSD), Physical Sciences Directorate (PSD
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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