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Software-Defined Networking (SDN) solutions to dynamically manage network congestion and improve communication efficiency. Research and develop topology-aware collective communication algorithms to optimize
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We are seeking a highly motivated postdoctoral researcher to join the Center for Nanoscale Materials (CNM) at Argonne National Laboratory. The successful candidate will contribute to the development of advanced scanning/transmission electron microscopy (S/TEM) methods for cutting-edge scientific...
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be to develop high fidelity simulations and/or algorithms to enable Bragg coherent diDraction imaging. We expect x-ray ptychography and coded aperture methods to play a fundamental role in creating a
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. The project will involve development of novel parallel algorithms to facilitate in-situ analyses at-scale for multi-million and multi-billion atom simulations. In this role, you can expect to work on enhancing
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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. These instruments and techniques support APS user programs and beamline scientists working in materials science, geology, and biology. The brain is among the most complex structures known, containing over 89 billion