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deployment, monitoring, and optimization of complex scientific data streaming workflows for current and future production infrastructures. The project will involve close collaboration with a team of systems
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or a related field. Extensive experimental expertise is essential. Additionally, expertise in the modeling of electrochemical processes is highly desirable. 0-3 years past Ph.D. work experience is
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environment Demonstrated ability to think independently and innovatively to develop creative solutions Strong organizational skills and attention to detail Ability to model Argonne’s core values of impact
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projects and work on a variety of projects simultaneously. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires an on-site presence
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facilities in partnership with the computational science community. We help researchers solve some of the world’s largest and most complex problems with our unique combination of supercomputing resources and
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, instrumentation, modeling, and data science Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field(s) of materials science, physics, computational science, or a related field
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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experiments. Develop reinforcement learning models to improve gate fidelity. Leverage CNM’s state-of-the-art facilities, including the nanofabrication cleanroom and the Quantum Matter and Device Lab’s dilution
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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communication skills, and ability to interact with people at all levels both within and outside the laboratory. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork