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integration, documentation, and collaborative development. Familiarity with parallelization and high-performance programming techniques such as MPI, OpenMP, multiprocessing, or distributed computing in Python
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
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the following areas is preferred, and an exceptionally strong candidate in a single area is also encouraged to apply. Relevant areas include: Parallel and distributed graph and or ML algorithms
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Requisition Id 17270 Overview: The Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking an exceptional Postdoctoral Researcher to advance programming systems
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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of vector query processing, serverless/just-in-time query execution, parallel and distributed data management, and data management systems on emerging hardware Passionate about inventing, building, and
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background in one or more of the following areas: computer architecture, high-performance computing, quantum computing systems, distributed and heterogeneous computing, runtime systems, or performance modeling
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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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and epigenetic manipulation of AML cells and massively parallel reporter assays to investigate gene regulation in leukemia. Computational analysis of these data will involve applying existing tools and