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Ph.D degree in electrical engineering, computer engineering, computer science, or a related discipline Demonstrated experience developing, training, and applying AI algorithms to physical sensor data
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Requisition Id 15751 Overview: The Advanced Computing in Health Sciences (ACH) section at the Oak Ridge National Laboratory is seeking qualified applicants for a Machine Learning Engineer position
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learning algorithms for engineering systems Programming experience in FORTRAN, C, or C++ and scripting experience in Python or similar languages Experience with parallel computing environments and Linux
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a particular emphasis on error-corrected methods for future fault-tolerant quantum computing. The algorithms will be designed to address key models of quantum materials, such as the Hubbard model
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advanced manufacturing processes. Demonstrated experience in the design and implementation of numerical algorithms in one or more high-level computing languages, preferably within a team that follows
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Neuromorphic computing or Spiking Neural Networks Machine learning, AI/ML algorithms, or scientific computing Strong programming skills in Python and/or C++. Preferred Qualifications: Ability to work
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learning on large-scale HPC systems Scalable and energy-efficient AI training algorithms Image reconstruction, segmentation, and spatiotemporal modeling High-performance computing for large-scale AI and
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within a multi-disciplinary research environment consisting of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing
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experimental facilities. You will be responsible for developing energy-efficient, physics-aware algorithms designed for distributed learning across both high-performance and edge computing environments. You will
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power electronics resources modeling, explore different intelligence algorithms to enhance ease of usage of simulations, and different applications of EMT simulations. Selection will be based