321 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions at Oak Ridge National Laboratory
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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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learned sent to designer staff. Works with US ITER document Control Center to ensure accuracy and completeness of drawings and other engineering design documents in the DCC system Provides other functions
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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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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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fabrication Machine learning (ML)/artificial intelligence (AI) coursework Experience with AI/ML libraries (TensorFlow, PyTorch) Special Requirements: Work involves various physical requirements and working
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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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experience, or a B.S. with 15 years relevant experience. Demonstrated experience engaging with U.S. Department of Energy (DOE) program offices and aligning work with their strategic priorities. Excellent
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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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to national security. This position resides in the National Security Program Office, Intelligence and Special Programs, National Security Sciences Directorate, at Oak Ridge National Laboratory (ORNL). As a U.S
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to learn new material and technology rapidly and put that learning into effective practice. Demonstrated ability to problem-solve and debug application code independently. Preferred Qualifications