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will focus on the design and implementation of photogrammetry and 3D computer vision algorithms to support high-volume and high-throughput scientific data applications, primarily with remote sensing
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Ph.D degree in electrical engineering, computer engineering, computer science, or a related discipline Demonstrated experience developing, training, and applying AI algorithms to physical sensor data
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-sensor fusion, and propagation modeling — to develop AI-enabled detection, classification, and triangulation algorithms for critical energy infrastructure applications. This position resides within
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Community (IC) mission areas. In addition to developing sensor systems across complex RF environments, you will develop prototype communication systems—implementing end-to-end transmitter/receiver chains
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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. Collaborate with multidisciplinary engineering teams to integrate control algorithms, sensor feedback, and human-machine interfaces. Conduct risk assessments and safety analyses for manipulator designs
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to develop AI-enabled, low-latency signal-processing algorithms for next-generation pixel detectors used in high-energy physics experiments. This position offers the opportunity to engage in cutting-edge
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Community (IC) mission areas. In addition to developing sensor systems across complex RF environments, you will develop prototype communication systems—implementing end-to-end transmitter/receiver chains
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Requisition Id 15490 Overview: The Multimodal Sensor Analytics group in the Electrification and Energy Infrastructure Division (EEID) is seeking a postdoctoral researcher with proven expertise in
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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