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images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed
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navigating immersive 3D virtual environments (e.g., Roblox, Minecraft). Implement a parallelized agent-driven framework where multiple LLM-powered agents operate concurrently to explore user-generated worlds
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fiscal oversight and efficiency of multiple projects in parallel. In collaboration with departmental leadership, establish scalable departmental operations infrastructure and procedures that will ensure
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will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in
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inversion of well logs acquired along arbitrary well trajectories, (b) in-well and inter-well formation evaluation, and (c) multi-core and parallel processing algorithms. Develop multi-well, formation
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the world. This evergreen posting represents multiple potential openings across ORNL’s high-performance computing ecosystem. Successful candidates will help architect, deploy, and maintain HPC systems
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across multiple temporal scales, from short-range to up to 10 days ahead, using recent advances in deep learning. A central component of this effort is Anemoi , a framework developed by the European Centre
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, Azure, GCP), Massive Parallelism paradigms (MPI, OpenACC, Accelerators) and more. You will be part of a team supporting all University-wide ARC services and national services such as NSF ACCESS, and
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systems, high-speed parallel file systems, and archival solutions critical to advancing scientific discovery and innovation. As part of ORNL’s leadership-class computing ecosystem, you will play a vital
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tools such as scientific computing, High Performance Computing (HPC), Big Data (Spark, DBMS), Machine Learning, cloud computing services (AWS, Azure, GCP), Massive Parallelism paradigms (MPI, OpenACC