171 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" positions at Oak Ridge National Laboratory in United States
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multiple types of sensing modalities, where this expertise is applied to solve critical national problems in energy and security. Demonstrated knowledge of emerging AI and machine learning techniques as
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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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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
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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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, or office support experience (or equivalent combination of education and experience). Proficient in office computer systems and software applications such as Microsoft Office/Outlook. Must work well in a team
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needs. By leveraging advanced simulations, machine learning, and data-driven insights, the group enables more effective operations aligned with evolving energy demands. The group also develops hydrologic
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) with questions related to this position. Major Duties/Responsibilities: Develop and apply machine learning models (ML) as surrogates for high-resolution process-based hydrologic models. Design and
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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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modeling, machine learning, and automated experimentation. Mentor and support Group Leaders to ensure excellence in research performance, staff development, inclusion, and cross‑disciplinary collaboration
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work to exciting research in multi-disciplinary domains alongside globally recognized experts. You will bring creative thinking, teamwork, and machine learning skills to bear as you develop new methods