Postdoctoral Research Associate

Oak Ridge National LaboratoryOak Ridge, TN
177d

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About The Position

The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral researcher with expertise in distributed intelligence, reasoning models, LLMs, workflow management, and distributed systems to contribute to the development of advanced decentralized intelligence techniques for scientific workflows deployed across heterogeneous computing resources. As a postdoctoral fellow at ORNL, you will join a dynamic team of researchers specializing in workflow management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer-the world's first exascale system. In this role, you will collaborate with leading scientists to design and implement distributed intelligence solutions tailored for large-scale scientific workflows in DOE environments. Your work will be pivotal in advancing the state of the art in resilient infrastructure by developing more efficient and adaptive techniques that maintain robust performance guarantees while optimizing resource utilization across the computing continuum. Additionally, you will investigate innovative approaches to optimize the balance between performance and resilience, considering the complexities of heterogeneous resources and varying workflow requirements across diverse scientific applications. The successful candidate will have the opportunity to use the computational power of the Frontier supercomputer to scale and validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE's SWARM project members to advance robust, performant, and fault-tolerant execution of DOE scientific workflows. This position offers a unique opportunity to make significant contributions to both theoretical and applied aspects of distributed intelligence, driving advancements in resilient, adaptive AI systems on a global scale.

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