46 phd-software-testing-scholarship Postdoctoral positions at Oak Ridge National Laboratory
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experiments in the SNS ring including experiment design, and data analysis. Develop software for data acquisition and analysis as needed. Perform simulations using a well-tested model of the SNS ring to
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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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will conduct research on irradiated materials using the capabilities of the Irradiated Materials Examination and Testing Facility and the Low Activation Materials Development and Analysis Laboratory
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analysis software. The prospective candidate will also have the opportunity to develop their own science that will complement the proposed DIB studies. Major Duties/Responsibilities: Study droplet interface
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by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in physics or a related field completed within the last 5 years
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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in professional organizations Basic Qualifications: A PhD in Mathematics, Applied Mathematics, Computational Science, or a related field completed within the last 5 years Preferred Qualifications
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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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professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant area with an education and a research track record in HPC/AI/edge systems and storage
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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