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scientific imaging. The primary responsibility of this position is designing and implementing sparse algorithms for large-scale scientific and numerical computations. The successful candidate will pursue
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mathematical representations of quantum states and processes, develop algorithms, and produce open-source scientific software Write peer-reviewed scientific articles and present research findings at major
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success Basic Qualifications: A PhD in
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@ornl.gov (For postdocs, use [email protected] ) with the position title and number referenced in the subject line. Instructions to upload documents to your candidate profile: Login to your account
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responses to environmental change. This position resides in the Ecosystem Processes Group in the Environmental Sciences Division at Oak Ridge National Laboratory (ORNL). The selected candidate will work with
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distributed codes using MPI, OpenMP, CUDA, ROCm, and related HPC technologies while bridging theoretical AI models with real hardware constraints. Cross‑Paradigm Integration(new optional emphasis): Explore how
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to accomplish multiple tasks within deadlines, and adapt to ever-changing needs Special Requirements: Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date of application
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with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate
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. The postdoctoral researcher will also be involved in developing formulations and processes for infiltrating preceramic polymer and organometallic compounds in fiber based preforms to manufacture ultrahigh
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models of gas transport and process behavior in industrial systems Collaborate with a team of scientists from across the national laboratory complex on modeling efforts Extend process flow modeling across