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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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principal investigators in writing proposals for new projects Adhere to requirements for protecting proprietary or sensitive information and follow ORNL cybersecurity policies and guidelines Basic
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laser deposition, characterization, analyzing data, and writing papers. Major Duties/Responsibilities: Conduct epitaxial synthesis of complex-oxide thin films and heterostructures by pulsed laser
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compilers and runtimes can unify classical, quantum, and analog execution models under a shared optimization framework. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or a closely
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qubit engineering to quantum algorithmic analysis to applications across the physical sciences (condensed-matter or high energy physics, data science). You will Interpret, report, and present research
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving