211 data-"https:"-"https:"-"https:"-"https:"-"J.-F" positions at Oak Ridge National Laboratory
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research spanning detector simulation, Spiking Neural Network (SNN) design, neuromorphic hardware, and data-rich experimental systems such as CMS pixel detectors, Timepix4, and novel photodetector
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solutions to compelling problems in energy and security. The Data Science & Visualization Group at Oak Ridge National Laboratory (ORNL) advances AI/ML research and delivers applied solutions that support high
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infrastructure, ensuring smooth data communication by managing and configuring network devices like routers, switches, firewalls, and wireless access points, monitoring network performance, identifying and
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experience. Understanding of biogeochemical and ecological processes. Programming experience in Fortran, python, R, or a related language. Experience in geospatial and/or time series data analysis. Evidence of
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technical leadership in AI security evaluation mechanisms. Required Qualifications Master’s Degree in Computer Science, Computer Engineering, Cybersecurity, or related fields with 7-10 years of experience
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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 analyze system performance statistical data to improve the quality of the network environment. Adhere to a customer serviced focused culture. Deliver ORNL’s mission by aligning behaviors, priorities
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professional office environment and ensure front desk areas remain organized and secure. Handle sensitive or confidential information with discretion. Maintain a consistent, reliable work schedule during core
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framework for driven and open quantum systems. Phenomenological modeling of dynamics/transport behaviors in complex systems, including strongly correlated electron systems. Experience in analyzing data from
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Postdoctoral Research Associate in the areas Artificial Intelligence (AI) for Integrated Hydrology Modeling. The successful candidate will have a strong background in computational science, data analysis, and