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: Experience in one more of the following areas: Mathematical tools for data analysis Numerical methods for differential and integral equations Modern machine learning software tools and frameworks
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advanced computational approaches, software engineering, high-performance computing, and an understanding of materials science, with an emphasis on metallurgy related to phase transformations and/or
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scientific outputs that may include peer-reviewed publications in top-tier water journals, professional scientific code/software contributions, and high-quality datasets. Candidates must also be willing
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research within past five years. Preferred Qualifications: Ability to work independently to design and deploy methods at scale. Familiarity with hardware-software co-design, memory hierarchies (DDR, HBM
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and
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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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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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changing needs Preferred Qualifications Experience in radiological risk assessment Experience in biokinetic model development Experience with Monte Carlo radiation transport software and applications
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-resolution microscopy, and in situ neutron or X-ray scattering and tomography methods. Strong background in computational and image-processing software, scientific programming, and high-performance computing