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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 14 hours ago
and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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. You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. An excellent scientific track record proven
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of capabilities such as AI training and inference at scale, and tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics
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conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry, Computational Science
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program is designed for candidates who have completed their PhD within the last two years and have experience as
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-reviewed venues and conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis