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other domains by designing scalable, transparent, and adaptable workflow systems. This role offers an opportunity to work with ORNL’s leadership-class computational resources, experimental facilities, and
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you access to resources that enable impactful, facility-scale innovation. If you're passionate about creating solutions that empower AI at scale, we encourage you to apply and help shape the future
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Research Associate to develop and apply computational technique for advanced manufacturing using high-performance computing resources. ORNL’s CCP conduct world-leading research and development in multi-scale
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multidisciplinary team of hydrologists, Earth scientists, and computational scientists to leverage leadership-class computing resources for large-scale model training, testing, and deployment. Contribute
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supercomputing resources. The candidate will also contribute to the development of large-scale identity and key management solutions. We are a leader in computational and computer science, with signature strengths
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, classification, and interpolation of pixel detector data. Exploration of spike-based data encoding/decoding strategies. Hyperparameter optimization using advanced computing resources (e.g., HPC clusters). Detector
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travel allowance and access to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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/Responsibilities: • Design and test novel quantum algorithms for materials simulations. • Develop resource estimates for implementing these algorithms on quantum hardware • Perform hybrid quantum-classical
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engineers, leveraging cutting-edge resources; most notably the Frontier supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research