27 distributed-algorithm-"EURAXESS" Postdoctoral positions at Oak Ridge National Laboratory in United States
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Requisition Id 16985 Overview: We are seeking a Postdoctoral Research Associate to join a large research team working on the development and implementation of novel algorithms for scientific
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. Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other related definitions. Knowledge of federated learning SOTA algorithms. Knowledge of distributed
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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. Knowledge of HPC matrix, tensor and graph algorithms. Knowledge on distributed algorithms using MPI and other frameworks such as NCCL. Knowledge of high-performance computing and its applications. Special
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). The successful candidate will contribute to the modeling, simulation, and co-design of next-generation Quantum-HPC (QHPC) architectures, with particular emphasis on integration of quantum and HPC distributed
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distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and
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navigation, trajectory planning, and point cloud mapping; and (3) deploy the developed algorithms on a physical mobile robot operating in GPS-denied, low-light, and geometrically repetitive environments
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computational models, systems, and AI/ML tools using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. In
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materials science applications and algorithms for OLCF supercomputers Develop and apply advanced, compute-intensive materials simulation methodologies to study the fundamental properties of molten salt