35 software-defined-network-postdoc Postdoctoral positions at Oak Ridge National Laboratory
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at scale. Experience in HPC and associated software development for applications, middleware, and/or system software. Flexibility to adapt to diverse R&D projects and tasks. Effective communicator in both
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: Experience in one more of the following areas: Mathematical methods for kinetic and/or fluid equations Multiscale problems and model reduction Modern machine learning software tools and frameworks
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machine learning software tools and frameworks Implementation of scalable numerical algorithms on HPC architectures Excellent written and verbal communication and interpersonal skills. The ability to obtain
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, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL). The qualified candidate will study, simulate and develop software for beam transport and beam dynamics in SNS superconducting linac
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on circular economy research Experience in working in the genetic algorithm and artificial neural networks is preferred. Experience in manufacturing process modeling of advanced manufacturing technologies
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development techniques (numerical methods, solution algorithms, programming models, and software) at scale (large processor/node counts). Experience with use of artificial intelligence and machine learning in
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descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other
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other MEERA Group industrial technical deployment (Better Plants) and Energy System Software Tools development projects. Help support the development of new resources, trainings, and tools to support
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software tools and frameworks Implementation of scalable numerical algorithms on HPC architectures Excellent written and verbal communication and interpersonal skills. The ability to obtain and maintain a
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, Scikit Learn, etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (Transformers). A broad