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complex projects and troubleshooting complex system issues and access problems. Ability to set priorities, learn new skills, and prioritize continuing professional development. Commitment to strong service
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. Experience with developing machine-learning surrogates for structure-property relationship, generative AI models, material representations, machine learning force-fields (especially extensions to spinful
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collaboration and coordination across instructor-led training (ILT), computer-based training (CBT), blended learning, qualification, and workforce development programs to promote consistency, alignment, and
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continuous learning. Operational Excellence and Compliance Champion safety, security, and ethical research practices; ensure compliance with ORNL policies and ESH&Q standards. Maintain clear internal and
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-body ab-initio methods for description of electronic, magnetic, and vibrational properties in a range of materials Expertise with artificial intelligence and machine learning approaches will be also
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Requisition Id 16695 Overview: As a Senior AI Architect at Oak Ridge National Laboratory (ORNL), you will operate at the intersection of advanced machine learning, software and systems
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Models: RLHF/RLAIF, online RL, self-play, open-ended discovery, reward modeling, curriculum/active learning, data selection, iterative post-training, safety alignment and guardrails. Foundation Models
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that combines mechanistic ecophysiology with AI, such as: Physics-informed machine learning and neutral networks to investigate plant physiological / abiotic relationships Bayesian statistics and neural and
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and prepare periodic summaries of equipment utilization, partner requests, response times, calibration status, lessons learned, and program improvement opportunities. Engineering measurement and
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-integrity . Basic Qualifications: PhD degree in Mechanical Engineering, physics, or related field, or a MS. Degree and two plus years of post-graduate experience. Applied experience in performing dynamic