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streams for reliable AI model training. Design of digital twins for process monitoring, fault diagnosis, and predictive maintenance in chemical plants. Key Responsibilities: Create and implement hybrid AI
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RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment
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twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g., compressors, reaction kettles
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
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and automated fault detection and diagnosis (AFDD) algorithms to buildings Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
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Postdoctoral position in Bioinformatics/Computational Biology (m/f/d) (full-time position 100 % ~ 38
diagnosis of IEIs and better understand cancer syndromes. These integrative analyses are central to translating genomic data into clinical insights (e.g., Haimel et al., J. Allergy Clin. Immunol. 2021
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machine learning tools for detection, diagnosis, and correction of sensor faults Report results in peer-reviewed publications Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with