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methods to work with a team of scientists in CSD to model chemical reactions important to determine the longevity of amorphous materials. That mechanistic information will be incorporated into process-based
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for simulating atomic nuclei, as well as preparing data and using machine learning models for investigating how the properties of atomic nuclei connect to fundamental questions in physics, such as constraining
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are especially interested in candidates with strong technical expertise in AI architecture design (e.g., Vision Transformers, foundation models, and federated learning), scalable computing on leadership-class
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Department of Energy (DOE). ORNL’s CCP conducts world-class research and development in multi-scale computational coupled physics, large scale data analytics and DL, and model-data integration at the DOE’s
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such as quantization, model pruning, approximate attention (linear and sparse) and proposing new mechanisms for tackling speed, accuracy, as well as energy issues, for large language mode (LLM) inferencing
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materials that may serve as model systems displaying quantum behaviors. It will also provide opportunities for collaboration with quantum computing efforts within the Quantum Science Center, guiding and
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United States respond to environmental disturbances. This position resides in the Watershed Systems Modeling (WSM) group in the Environmental Sciences Division (ESD), Oak Ridge National Laboratory (ORNL). ESD is
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of agentic AI for science, scientific reasoning, federated & collaborative learning, and reinforcement learning (RL) for self-improving models, in the context of leadership scientific workflows and
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photosynthesis to join the new pilot study of Generative Pretrained Transformer for genomic photosynthesis (GPTgp). The GPTgp project aims to develop a foundational holistic model of photosynthesis that will scale
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Laboratory (ORNL). Major Duties/Responsibilities: Develop models and software for the design and optimization of sensor networks in complex systems, such as water treatment systems Develop physics-based and