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informed of class logistics. Use the Learning Management System (LMS) for monitoring registrations, determining class assignments, setting delivery schedules, printing rosters, and verifying training records
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(PMI) Science Focus Area and the GPTgp (Generative Pretrained Transformer for Genomic Photosynthesis) project. This position focuses on developing machine learning pipelines, AI-driven scientific
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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such as federated learning. Provenance and Reproducibility Frameworks: Build systems that enable detailed provenance tracking, schema validation, and auditable workflows to ensure trustworthy and
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Requisition Id 15885 Overview: We are seeking a Postdoctoral Research Associate – Simulation and Machine Learning for Composite Manufacturing who will focus on developing physics-based simulation
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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for every task, and never stop learning. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal
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must be able to acquire and maintain appropriate training and qualifications to work in these areas and follow all safety instructions Excellent written and oral communication skills Motivated self
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environments for several hours at a time; lifting equipment up to 30 lbs) Ability to proactively work independently and as part of a team Demonstrated ability and willingness to acquire new knowledge and learn
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. Preferred Qualifications Familiarity with techniques for AI-on-AI adversarial evaluation, including reinforcement learning-based adversarial testing setups. Expertise in designing systems that support red