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Field
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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on emerging architectures and performance for advanced computing. This position resides in the Architectures and Performance Group (APG) in the Computer Science and Mathematics Division at Oak Ridge National
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. Work description You are expected to explore both software architecture and software design in the era of artificial intelligence, addressing both how AI can support engineering practices (AI4SE) and how
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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learning, reinforcement learning, transformer architectures and large language models. - Analytical many-body and quantum information theory: replica field theory approaches to monitored and noisy quantum
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create knowledge, innovations, and solutions that help move the world forward. Faculty Architecture & the Built Environment The Faculty of Architecture and the Built Environment has a leading role in
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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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ideal for a researcher who possesses working fluency across both computational AI architectures and physical lab automation. We are seeking someone with an eagerness to master missing domains and a strong
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familiar with contemporary construction techniques and have an interest in 20th-century construction techniques or vernacular architecture. Experience in Life Cycle Assessment (LCA), Building Information
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demonstrated research experience with foundation models , including the evaluation and adaptation of pre-trained models, fine-tuning strategies, and the development of new model architectures or learning